Author: admin

Posted on

The Changing Nature of Research in Higher Education

Research in higher education looks very different today than it did even ten years ago.  Academics who, not so very long ago, were well acquainted with physical library study spaces and large collections of peer-reviewed academic journals, find themselves in a digitized world of research with unprecedented access to information and virtual repositories of human meaning-making activity.  The nature and culture of research in higher education is shifting, including that which is considered “worthy” content to explore when conducting research in all kinds of disciplines.  One need look no further than the APA reference guide and the ever-expanding list of possible resources (e.g.. YouTube videos and TED talks, podcasts, blog posts, etc.) to note that the “rules” of research are expanding, and must expand, alongside our access to information.

jesadaphorn/Shutterstock.com

As a current doctoral student (and someone who received my initial graduate degree a decade ago), I am curious about the ways the research sector of higher education has changed over time. How are undergraduate students being taught to conduct research?  What kind of shifts have been made due to new tools and technology platforms that assist in the research process?  What cultural shifts are happening in graduate and doctoral programs, and are these cultural shifts impacting research strategy? 

Jonbloed et al. (2008) posit that higher education has an expanding set of stakeholders and thus a continually shifting societal expectation of what a university’s public obligation is.  Early universities provided education exclusively for clergy and societal elites, but over the centuries, higher education has been democratized such that there are many invested parties and participants with competing paradigms and priorities. Indeed, one of the major, ongoing, accelerated shifts in higher education is the diversification of students, staff, and faculty and the role that universities can/should play as advocates of–and vehicles for–social justice (Brennan & Teichler, 2008).  We also now live in a “knowledge society” where knowledge is considered the solution to everything and the key to personal and societal advancement (Jonbloed et al., 2008).  Thus, higher education institutions (HEIs) are driven to make teaching and research more publicly accountable, often restructuring programs and creating new ones to meet modern societal demands and forfeiting, or “reorienting,” long standing academic norms and values along the way (Jonbloed et al., 2008).

Even the doctorate degree, a terminal, research-based degree program which is typically the highest academic degree that can be awarded by a university, isn’t immune to change.  There is an increasing demand for doctoral programs to become more relevant, to produce academics with transferable skills in their field in addition to research skills, and to even be more sensitive to issues of employability that extend beyond creating new academics who scarcely step outside the “ivory tower” of a university campus (Park, 2005).  This requires attention to the course structure and modality of a doctoral program, the quality of the mentorship provided, the diversity of students within the program, and an expansion of that which is considered sufficient, valuable evidence of research contributions in a given field.

At the undergraduate level, much focus is given to the development of research skills as a form of information or digital literacy.  K-12 schools and districts across the United States differ greatly in their approach to teaching digital literacy skills.  Thus, undergraduate students at HEIs come into lower division classes with a wide range of background and abilities (or lack thereof) informing their approach to research.  In a case study conducted at Texas Christian University (TCU) by Huddleston et al. (2019), faculty were surveyed to determine what research skills they felt were most needed and valuable for undergraduate students to have, and which skills undergraduate students tended to struggle with most.  A list of nine core skills for research success was produced based on faculty responses:

  1. Topic selection
  2. Search strategy
  3. Finding resources
  4. Differentiating source types
  5. Evaluating sources
  6. Synthesizing information
  7. Summarizing information
  8. Citing sources
  9. Reading and understanding citations

Perhaps unsurprisingly, faculty overwhelmingly felt that the skill they most wanted students to master by the time they graduated was the ability to critically evaluate information and sources.  This was, however, also found to be the weakest skill that undergraduate TCU students possessed, and that they were least likely to be able to do at a satisfactory level upon graduation (Huddleston et al., 2019).  It is no coincidence that the ability to think critically about an information source is needed now more than ever due to the overwhelming amount of information and sources available on the world wide web.  While access to valuable, credible sources of information expands, students need to be able to recognize “worthy” material in dynamic ways which allow them to differentiate their source types appropriately.  Certainly not all valuable research material is limited to the contents of academic journals, but neither is every blog post worthy of scholarly consideration. In this case study, Huddleston et al. (2019) note that the university library/librarians are important resources and guides when it comes to information literacy instruction, and a number of suggestions were made to help increase the visibility of librarians at the department level, leveraging their knowledge and training alongside faculty in a collaborative approach to teaching undergraduates needed research skills.

There is no denying that a certain level of digital and informational literacy is essential in all areas of higher education given that “research outputs across the academic disciplines are almost exclusively published electronically,” and therefore “organizing and managing these digital resources for purposes of review…are now essential skills for graduate study and life in academia.” (Lubke et al., 2017, p. 285) Of course, in the year 2021, there are also a myriad of digital tools available that not only assist in the research process, but make it easier to practice information literacy and grow a researcher’s individual technical savvy. Assuming the literature review (i.e. research paper) is the most frequent research-based activity conducted in higher education, especially at the graduate level, Lubke et al. (2017) propose a simple, 3-step framework which can become the essential workflow for a paperless research project.

Lubke et al. (2017)

As the image suggests, stage one begins with selecting a digital tool to store and analyze sources.  Some suggested platforms include Zotero, EndNote, F1000 Workspace, RefWorks, and Mendeley.   Each tool has its own strengths and weaknesses, but generally speaking, each is an example of a digital tool that assists researchers in methodically storing and organizing possible source material for consideration, both in the current research process and for possible future use (e.g. dissertation).  Once sources have been selected and stored, researchers may then move to stage two where they may read, annotate, and analyze their sources.  This is where weak sources may be removed from consideration and where important pieces of information are mined and commented on in preparation for creating an academic argument (Lubke at al., 2017). In the annotation phase, digital tools like GoodReader can be used to take notes and highlight a text; then, annotated versions of sources may be saved separately from the original.  Finally, in stage three, researchers may choose to employ Qualitative data analysis software (QDAS) like QSR NVivo to synthesize themes and pull together information from across sources, ultimately drawing conclusions for publication.

The nature of research in higher education–and really, higher education itself–has changed drastically over the course of the last couple of decades.  Higher education is expanding in its scope and purpose, and there is increasing demand for academic research to have immediate, practical value. When conducting research, the most frequent problem faced by students and academics at all levels is what to do with the vast amounts of information we now have access to: how to source it, organize it, and analyze it critically.  Direct instruction in digital and information literacy continues to be a need in postsecondary education (both undergraduate and graduate), but there are a number of tools available that can be powerful aids in the research process, expanding our knowledge base and extending our capacity to think critically about sources, thus also expanding our potential for innovation.  There is no doubt that the nature of research will continue to evolve alongside the digital world…are we ready to consider the possibilities?

References

Brennan, J. & Teichler, U. (2008).  The future of higher education and of higher education research. Higher Education, 56(3), p. 259-264. https://doi.org/10.1080/13583883.2003.9967102

Huddleston, B., Bond, J., Chenoweth, L., & Hull, T. (2019). Faculty perspectives on undergraduate research skills: Nine core skills for research success. Reference & User Services Quarterly (59)2, pp. 118-130. 

Jonbloed, B., Enders, J., & Salerno, C. (2008). Higher education and its communities: Interconnections, interdependencies and a research agenda. Higher Education, 56(3), p.303-324.  https://doi.org/10.1080/13583883.2003.9967102

Lubke, J., Britt, V., Paulus, T., & Atkins, D. (2017).  Hacking the literature review: Opportunities and innovations to improve the research process. Reference and User Services Quarterly (56)4, p. 285-295.

Park, C. (2005). New variant PhD: The changing nature of the doctorate in the UK. Journal of Higher Education Policy and Management 27(2), p.189–207. https://www.tandfonline.com/doi/abs/10.1080/1360080050012006

Posted on

Assessment in higher education during COVID-19 and beyond: Will it ever be the same?

Ridofranz/Getty Images

Perhaps the word “unprecedented” has been overused in recent months, but it consistently seems to be the most fitting word to express the seismic shifts in all areas of life that have occurred during the COVID-19 pandemic. As K-12 and higher education institutions worldwide have grappled with rapid pivots to online teaching and learning (and have continued in these blended and fully remote modalities for much longer than anticipated), academics are now taking a moment to reflect on the past year and its lasting implications for the world of education.  After all, as business theory would posit, disruption leads to innovation.

As an educator interested in online teaching/learning in post-secondary education, I would specifically like to explore how the last year of remote learning has impacted assessment strategies in higher education. How have widespread shifts to online teaching/learning impacted college students’ abilities to demonstrate competency in varied and student-driven ways?  Higher education is notoriously “old school,” and post-secondary classes are most frequently  lecture-based, led by instructors who are slower to adapt to more progressive, student-driven pedagogies.  And yet, as universities across the U.S. have made college and graduate school entrance exams like the SAT, ACT, and GRE optional for applicants in 2020 and 2021, a world beyond high stakes standardized testing can perhaps be imagined now more than ever.

Higher education instructors worldwide are already engaging in this issue and offering recommendations for ongoing change.  Perhaps surprisingly, some of the first publications I encountered came from educators in the graduate medical school community in both Australia and Pakistan. This was particularly striking since the medical sciences require lab work and clinical assessments which are particularly challenging to address in remote situations, as well as the fact that the medical sciences have long required high stakes testing at many stages of a medical student’s training.

According to Torda (2020), many medical school instructors in Australia have moved to lower the stakes of traditional written or multiple choice exams delivered online during the pandemic.  At the same time, a shift has been made to put more weight on multi-sourced feedback and student portfolios.  Where clinicals are concerned, simulation platforms such as the OSPIA (Online Simulated Patient Interaction and Assessment) system have been leveraged to bridge the gap until in-person clinicals may safely resume.  Another significant shift has been an emphasis on measuring a student’s ability to exhibit key professional skills, known in the medical community as “Entrustable Professional Activities,” over and above written examinations (Torda, 2020)..  In other words, students are being assessed on their ability to apply their learning in professionally relevant contexts.  Some of these skills include, but are not limited to, recommending and interpreting common diagnostic and screening tests, providing a (virtual) oral presentation of a clinical encounter, forming clinical questions and retrieving evidence to advance patient care, and collaborating with professional colleagues (Torda, 2020).  It was noted that, taken as a whole, these measures go a long way toward easing test anxiety and motivations to cheat in an otherwise high stakes, demanding field of study (Torda, 2020).

Additional examples of altered assessment strategies in the medical community have been reported in Pakistan.  Similar to Torda (2020), Khan and Jawaid (2020) posit that the pandemic has necessitated lowering the stakes of online-proctored, traditional exams.  The authors advocate for the use of student portfolios and video evidence of professional tasks completed, as well as synchronous open book exams.  The authors note that the aim of synchronous open book exams “…is to assess the ability of students to analyze and solve a problem, [and to] assess critical thinking and creativity. With open book exams taken in real time, the issues of cheating can be minimized.” (Khan & Jawaid, 2020, p. 109)

Changes in higher education assessment have also been reported in the United States. In June of 2020, Natasha Jankowski, in partnership with the National Institute for Learning Outcomes Assessment (NILOA), spearheaded a higher education survey meant to capture “a snapshot of assessment-related changes made during Spring 2020 in response to the sudden shift to remote instruction…” (Jankowski, 2020, p. 3). The survey included responses from faculty and staff at 624 different institutions, both public and private, with representation from all 50 states. The survey sought to record learning changes that higher education instructors were making, the impacts of those changes on assessment culture, and the role of student voice in the decisions (Jankowski, 2020).  The survey results showed that 97% of respondents made learning, instructional, and assessment changes of some kind during Spring 2020. Changes included modifying assignments and assessments, allowing flexibility in assignment deadlines, shifting to a pass/fail grading model, and modifying assessment reporting deadlines.  Though some respondents made changes that included accepting alternative assignments, this was a less often made change (Jankowski, 2020).  The survey also showed “…that assessment-related changes were undertaken to address student needs” (p. 3).  However, these changes may have had more to do with faculty/staff perception of student needs as opposed to action taken in direct response to student reports: “Information gathered from students was less likely to influence decisions on what to change, and students were less likely to be asked to identify their needs prior to decisions being made.” (p. 3) Consequently, it might be hard to define many of these changes in assessment as authentically “student-driven.” 

Nevertheless, it seems that the pandemic has disrupted “business as usual” in higher education such that many of the changes reported above may in fact have lasting impact with increasing opportunity for student voice to take a front seat in decision-making.  Dr. Funmi Amobi of Oregon State University’s Center for Teaching and Learning puts forth compelling arguments in favor of  “reimagining” assessment in higher education in light of the lessons we’ve learned in the pandemic (Amobi, 2020).  Amobi asserts that the radical move to remote instruction has “refocused attention on improving assessment practices to alleviate student stress and anxiety, emphasize learning, and redress inequities in student success.” (par. 2)  The author goes further and provides seven practical strategies for reimagining assessment in higher education.  Though these strategies can certainly be used effectively in remote learning environments, they are not only meant to solve problems related to online teaching and learning.  The strategies presented by Amobi (2020) should be taken seriously by all higher education instructors wanting to diversify their approach to assessments and create more student-centered learning experiences: 

  1. Use short, weekly quizzes to assess students formatively, and consider making the quizzes cumulative so that they may contribute to a summative assessment score.
  2. Ask for justification on multiple choice tests and grade the response instead of the answer.
  3. Create opportunities for collaborative, group tests.
  4. Have students construct exam questions themselves as a way of reviewing and exercising higher order thinking skills; then, include many of the student questions on the exam.
  5. Allow for notes or a study card and have students submit the prepared materials for credit along with the actual exam.
  6. Utilize practice tests.
  7. Spend time reviewing exams to address misunderstandings and improve future performance; consider giving credit for thoughtfully corrected exams where learning is evident.

In each of the reviewed publications, certain recurring themes were readily apparent: 1) it may be high time for colleges and universities to rethink the value of high stakes testing 2) varied assessment strategies allow for a more effective presentation of student learning 3) assessment is part of the overall learning process and should not be divorced from student voice 4) varied assessment strategies reduce test anxiety and the motivation to cheat (the ladder being oft-cited as a obstacle in online assessment). 

We must avoid the underlying assumption that more technology is needed in order to solve the problems that technology introduces.  In other words, as the pandemic continues to require extended engagement in remote teaching, higher education instructors must not assume that the only way to assess online is to find a way to virtually proctor the same exam that would normally be given in a physical classroom (Kumar, 2020).  Instead, educators at all levels may take this opportunity to make meaningful changes to their use of assessments, both now and into the future, thinking critically and creatively about how to best meet students where they’re at.  

References:

Amobi, F. (2020, November 12). Reimagining assessment in the pandemic era: Comprehensive assessment of student learning. OSU Center for Teaching and Learning. https://blogs.oregonstate.edu/osuteaching/2020/11/12/reimagining-assessment-in-the-pandemic-era-comprehensive-assessment-of-student-learning/

Jankowski, N. A. (2020). Assessment during a crisis: Responding to a global pandemic. National Institute for Learning Outcomes Assessment. https://public.uhcl.edu/education/centers-initiatives/planning-assessment/documents/niloa-covid-assessment-report.pdf

Khan, R. A. & Jawaid, M. (2020). Technology Enhanced Assessment (TEA) in COVID 19 Pandemic. Pakistan Journal of Medical Sciences 36, 108-110. 10.12669/pjms.36.COVID19-S4.2795

Kumar, R. (2020). Assessing higher education in the COVID-19 era.  Brock Education Journal 29(2), 37-4. https://journals.library.brocku.ca/brocked

Torda, A, (2020). How COVID‐19 has pushed us into a medical education revolution. Internal Medicine Journal 15(9), (1150-1153).  https://doi.org/10.1111/imj.14882

Posted on

Digital Learning Mission Statement

As a developing leader in the digital education space, it’s vital to understand and articulate what guiding principles and values will shape my priorities and research in the present and also guide my work in the future.  These same values should, of course, be reflected in my own digital footprint in as much as they inform my approach to leadership.    

As a digital citizen advocate (ISTE Standard 7) and admissions official in higher education, I hope to elevate and address issues of access and equity, champion authenticity and integrity in digital spaces, and empower students, faculty, and staff to hold themselves accountable for their actions, roles and responsibilities in digital spaces.   

Access:   

Issues pertaining to access and equity in the higher education admissions world have long persisted, but they’ve been especially well-documented in recent years as controversy after controversy has made headlines.   

In 2019, a highly-publicized admissions scandal known as Operation Varsity Blues revealed conspiracies committed by more than 30 affluent parents, many in the entertainment industry, offering bribes to influence undergraduate admissions decisions at elite California universities.  The scandal was not, however, limited to misguided actions of wealthy, overzealous parents; it included investigations into the coaches and higher education admissions officials who were complicit (Greenspan, 2019).  This event—and others like it—highlight the fact that admissions decisions are not always objective and merit-based, and that those with the resources to game the system often do.  

Unfortunately, there are many ways in which bias and inequity infiltrate the admissions process and undermine the accessibility of a high-quality college education.  Standardized tests like the SAT or ACT for undergraduate admissions and the GRE or GMAT for graduate admissions come with their fair share of concerns.  Research has oft-revealed how racial bias affects test design, assessment, and student performance, thus bringing biased data into the admissions process to begin with (Choi, 2020).    

That said, admissions portfolios without standardized test scores have one less “objective” data point to consider in the admissions process, putting more weight on other more subjective pieces of an application (essays, recommendations, interviews, etc.). Most university admissions processes in the U.S.—both undergraduate and graduate—are human-centered and involve a “holistic review” of application materials (Alvero et al, 2020).  A study by Alvero et al exploring bias in admissions essay reviews found that applicant demographic characteristics (namely gender and household income) were inferred by reviewers with a high level accuracy, opening the door for biased conclusions drawn from the essay within a holistic review system (Alvero et al., 2020).  

It should go without saying that higher education institutions (HEIs) must seek to implement equitable, bias-free, admissions processes that guarantee access to all qualified students and prioritize diverse student bodies.  Though technology may not—and likely should not, on its own—be able to offer a comprehensive solution to admissions bias, there are certainly some digital tools that, when utilized thoughtfully by higher education admissions professionals, can assist in the quest to prioritize equitable admissions practices, addressing challenges and improving higher education communities for students, faculty, and staff alike (ISTE standard 7a).  

Without the wide recruiting net and public funding that large State institutions enjoy, the search for equitable recruiting/admissions practices and diverse classes may be hardest for small universities (Mintz, 2020). Taylor University—a small, private liberal arts university in Indiana—has turned to AI and algorithms for assistance in many aspects of the admissions and recruiting process.  Platforms such as the Education Cloud by Salesforce “…use games, web tracking and machine learning systems to capture and process more and more student data, then convert qualitative inputs into quantitative outcomes” (Koenig, 2020).    

Understandably, admissions officials want to admit students who have the highest likelihood of “succeeding” (i.e. persisting through to graduation).  Noting that predictive tools must also account for bias that may exist in raw data reporting (like “name coding” or zip code bias), companies with products similar to the Education Cloud market fairer, more objective, more scientific ways to predict student success (Koenig, 2020).  As a result, HEIs like Taylor are confidently using these kinds of tools in the admissions process to help counteract biases that grow situationally and often unexpectedly from how admissions officers review applicants, including an inconsistent number of reviewers, reviewer exhaustion, personality preferences, etc. (Pangburn, 2019).   

Additionally, AI assists with more consistent and comprehensive “background” checks for student data reported on an application (e.g. confirming whether or not a student was really an athlete) (Pangburn, 2019). Findings from the Alvero et al. (2020) study suggest that AI use and data auditing might be useful in informing the review process by checking potential bias in human or computational readings (Alvero et al, 2020).   

Regardless of its specific function in the process, AI and algorithms have the potential to make the admissions system more equitable by identifying authentic data points and helping schools reduce unseen human biases that can impact admissions decisions while simultaneously making bias pitfalls more explicit.  

Without denying the ways in which technology has offered significant assistance to—and perhaps progress in—the world of higher education admissions, it’s still wise to think critically about the function of AI and algorithms in order to ensure they’re helping more than they’re hurting.  There is a persistent and reasonable concern among digital ethicists that AI and algorithms simply mask and extend preexisting prejudice (Koenig, 2020).  It is dangerous to assume that technology is inherently objective or neutral, since technology is still created or designed by a human with implicit (or explicit) bias.  As author Ruha Benjamin states in Race After Technology: Abolitionist Tools for the New Jim Code (2019), “…coded inequity makes it easier and faster to produce racist outcomes.” (p. 12) Thus, there is always a balance to be struck where technology is concerned. 

As an admissions official at a small, private, liberal arts institution, I am well aware of the challenges presented to HEI recruitment and admissions processes in the present and future, and am heartened to consider the possibilities that AI and algorithms might bring to the table, especially regarding equitable admissions practices and recruiting more diverse student bodies.  However, echoing the sentiments of The New Jim Code, I do not believe that technology is inherently neutral, and I do not believe that the use of AI or algorithms are comprehensive solutions for admissions bias.  Higher education officials must proceed carefully, thoughtfully, and with the appropriate amount of skepticism in order to allow tech tools to reach their fullest potential in helping address issues of access, equity, and bias in higher education admissions (ISTE standard 7a).  

Authenticity:   

Anyone with a digital footprint has participated in creating—knowingly or unknowingly—a digital identity for themselves.  Virtual space offers people the freedom “…to choose who they want to be, how they want to be, and whom they want to impress, without being constrained by the norms and behaviors that are desirable in the society to which they belong” (Camacho et al., 2012, p. 3177).  The internet provides new opportunities for spaces for learning, working, and socializing, and all of these spaces offer opportunities for identity to be renegotiated (Camacho, 2012). It is a worthy—if not simple—endeavor to pursue authenticity and integrity within any kind of digital identity, digital media representation, or online interaction.  

Interactive communication technologies (ICTs) complicate meaningful pursuits of authenticity. These digitally-mediated realms of human interaction challenge what we see as authentic and make it harder to tell the difference between what is “real” and what is “fake” (Molleda, 2010).  One need look no further than “reality” TV, social media personas, and journalistic integrity in the era of “fake news” to understand that not all claims of authenticity in media are substantive.   

This does not mean, however, that authenticity in digital space fails to have inherent value or is impossible to achieve.  An ethic of authenticity goes beyond any kind of plan, presentation, or strategic marketing campaign; authenticity is about presenting the essence of what already exists and whether (or not) it has the ability to live up to its own and others’ expectations and needs (Molleda, 2010).  Exercising authenticity includes making informed decisions about protecting personal data while still curating the digital profile one intends to reflect (ISTE Standard 7d).  Exercising authenticity also contributes to a wise use of digital platforms and healthy, meaningful online interactions (ISTE standard 7b).  

In a comprehensive literature review, Molleda (2010) found that several pervasive themes, definitions, and perceptions of authenticity consistently surfaced across a variety of disciplines.  Taken as a whole, Molleda (2010) asserts that these claims may be used to “index” or measure authenticity to the extent that they are present in any given communication or media representation.  Some of these key aspects of authenticity include:  

  1. Being “true to self” and stated core values  
  2. Maintaining the essence of the original (form, idea, design, product, service, etc.)  
  3. Living up to others’ expectations and needs (e.g. delivering on promises)  
  4. Being original and thoughtfully created vs. mass produced  
  5. Existing beyond profit-making or corporate/organizational gains  
  6. Deriving from true human experience  

Molleda (2010) concludes that consistency between “the genuine nature of organizational offerings and their communication is crucial to overcome the eroding confidence in major social institutions” (p. 233). I for one hope to continue embodying an ethic of authenticity in both my personal and professional work—in digital spaces and otherwise—in order to set the stage for that consistency and to bolster societal confidence in the institution I’m a part of.  

Accountability  

The digital realm is an extended space where human interactions take place, and the volume of interactions taking place in digital spaces is only increasing.  As with any segment of human society, human flourishing, creativity, and innovation takes place in spaces where people feel safe and invested in the community in which they find themselves. Thus, as a digital leader, it is important to empower others to seriously consider their individual roles and responsibilities in the digital world, inspiring them to use technology for civic engagement and improving their communities, virtually or otherwise (ISTE standard 7a).  

Humans do not come ready-made with all of the savvy needed to engage with media and online communications in wise ways.  Media literacy education is needed to provide the cognitive and social scaffolding that leads to substantive, responsible civic engagement (Martens & Hobbs, 2015).  Media literacy is also a subset of one’s own ethical literacy, which is the ability to articulate and reflect upon one’s own moral life in order to encourage ethical, reasoned actions.  As a digital citizen advocate and marketing professional, I hope to support educators in all kinds of contexts—both personal and professional—to examine the sources of online media, be mindful consumers of online content, and consistently identify underlying assumptions in the content we interact with (ISTE standard 7c).  In an effort to be digitally wise and to “beat the algorithm” in digital spaces (both literally and metaphorically speaking), we must self-identify potential echo chambers and intentionally seek out alternative perspectives.  This requires a commitment to media literacy education in all kinds of formal and informal environments.    

Media literacy education equips educational leaders and students to foster a culture of respectful, responsible online interactions and a healthy, life-giving use of technology (ISTE standard 7b).  According to Hobbs (2010), media literacy is a subset of digital literacy skills involving:  

  1. the ability to access information by locating and sharing materials and comprehending information and ideas  
  2. the ability to create content in a variety of forms, making use of digital tools and technologies;   
  3. the ability to reflect on one’s own conduct and communication by applying social responsibility and ethical principles; (ISTE standard 7b)  
  4. the ability to take social action by working individually and collaboratively to share knowledge and solve problems as a member of a community; (ISTE standard 7a)  
  5. the ability to analyze messages in a variety of forms by identifying the author, purpose, and point of view and evaluating the quality and credibility of the content. (ISTE standard 7c)   

In a study conducted with 400 American high school students, findings showed that students who participated in a media literacy program had substantially higher levels of media knowledge and news/advertising analysis skills than other students (Martens & Hobbs, 2015).  Perhaps more importantly, information-seeking motives, media knowledge, and news analysis skills independently contributed to adolescents’ proclivity towards civic engagement (Martens & Hobbs, 2015), and civic engagement naturally requires dialogue with others within and outside of an individual’s immediate circle.  In other words, the more students were able to critically consider the content they were consuming and the motives behind why they were consuming it, the more they wanted to engage with alternative perspectives and be active, responsible, productive members of a larger community (ISTE standard 7a).  

This particular guiding principal is large in scope; it’s importance and relevance isn’t limited to a specific aspect of my professional context as much as it helps define an ethos for all actions, communication, and consumption that takes place in the digital world.  In order to hold ourselves accountable for our identities and actions online we must exercise agency.  The passive internet user/consumer is the one most likely to get caught in an echo chamber, develop destructive online habits, and communicate poorly in virtual space. The digitally wise will make consistent efforts to challenge their own thinking, create safe spaces for communication, intentionally seek out alternative voices, and actively reflect on their contributions to an online community, ultimately making digital spaces a little bit better than when they found them.  

References:  

Alvero, A.J., Arthurs, N., Antonio, A., Domingue, B., Gebre-Medhin, B., Gieble, S., & Stevens, M. (2020). AI and holistic review: Informing human reading in college admissions from the proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 200–206. Association for Computing Machinery. https://doi.org/10.1145/3375627.3375871.  

Benjamin, R. (2019).  Race after technology: Abolitionist tools for the New Jim Code. Polity.  

Camacho, M., Minelli, J., & Grosseck, G., (2012). Self and identity: Raising undergraduate students’ awareness on their digital footprints. Procedia Social & Behavioral Sciences, 46, 3176-3181.  

Choi, Y.W. (2020, March 31). How to address racial bias in standardized testing. Next Gen Learning. https://www.nextgenlearning.org/articles/racial-bias-standardized-testing  

Greenspan, R. (2019, May 15). Lori Loughlin and Felicity Huffman’s college admissions scandal remains ongoing. Here are the latest developments. Time. https://time.com/5549921/college-admissions-bribery-scandal/  

Hobbs, R. (2010). Digital and media literacy: A plan of action. The Aspen Institute Communications and Society Program & the John S. and James L. Knight Foundation. https://knightfoundation.org/reports/digital-and-media-literacy-plan-action/  

Koenig, R. (2020, July 10). As colleges move away from the SAT, will algorithms step in? EdSurge. https://www.edsurge.com/news/2020-07-10-as-colleges-move-away-from-the-sat-will-admissions-algorithms-step-in  

Martens, H. & Hobbs, R. (2015). How media literacy supports civic engagement in a digital age.  Atlantic Journal of Communication, 23, 120–137.  

Mintz, S. (2020, July 13). Equity in college admissions. Inside Higher Ed. https://www.insidehighered.com/blogs/higher-ed-gamma/equity-college-admissions-0  

Molleda, J. (2010). Authenticity and the construct’s dimensions in public relations and communication research. Journal of Communication Management,14(3), 223-236. http://dx.doi.org.ezproxy.spu.edu/10.1108/13632541011064508   

Pangburn, D. (2019, May 17). Schools are using software to help pick who gets in. What could go wrong? Fast Company. https://www.fastcompany.com/90342596/schools-are-quietly-turning-to-ai-to-help-pick-who-gets-in-what-could-go-wrong  

Posted on

Student Flourishing in the Virtual Classroom

Image Source, Medium.com

There is no doubt that the COVID-19 pandemic has greatly accelerated the rate at which schools and universities of all shapes and sizes have had to move to online teaching and learning modalities, even if only as a short-term conduit for allowing formal education to continue in these unprecedented times.  There is also no doubt that this emergency shift to online teaching has left many concerned about overall student well-being including screen fatigue, issues of access and equity, teacher readiness, social-emotional support in a digital environment, and the overall efficacy of the educational endeavor for students of all ages in digital mediums.  Is there a light at the end of the tunnel?  Or might there already be some twinkle lights strung up along the tunnel walls guiding the way? 

In this post I’d like to explore some of the evidence that already exists in support of student flourishing—particularly at the postsecondary level—in hybrid or fully online programs, as well as what best practices can be used to support student well-being in all online teaching/learning endeavors, during COVID-19 and beyond.  Thankfully, the pandemic didn’t bring about the dawn of online pedagogy in higher education, and postsecondary educators have places to turn in order to think critically (and perhaps hopefully) about student success and well-being, be it academic or personal, in the digital classroom.

Evidence of Flourishing:

Few would argue that an in-person classroom experience can be identically replicated online.  In fact, those who attempt to do so have probably done so with disappointing results.  But perhaps educators shouldn’t necessarily be trying to replicate a physical classroom experience in an online environment.  Rather, they should think of the virtual classroom as a new endeavor; it is a new context with new possibilities to explore, and online pedagogy may bring new teaching/learning benefits to the table that a physical classroom lacks. 

Indeed, there’s evidence to suggest that a hybrid of in-person and online teaching may be the very best approach to postsecondary learning—with or without a pandemic—as it capitalizes on the “best of both worlds.”  In an extensive, multi-year case study conducted at the University of Central Florida in 2004, research showed that student success in blended programs (success being defined as achieving a C- grade or higher) actually exceeded the success rates of students in either fully online or fully face-to-face programs (Dziuban et al, 2004).  Furthermore, in a meta-analysis of studies on online and hybrid learning conducted by the U.S. Department of Education in 2010, it was reported that students in online and hybrid learning programs had more gain in their learning when compared to face-to-face modalities, and students in hybrid learning courses had the largest gains in their learning among their peers in all delivery formats (Means et al., 2010).  In yet another study (Chen & Chiou, 2014) measuring the learning outcomes, satisfaction, sense of community and learning styles of 140 second-year university students in Taiwan, results showed that students in a hybrid course had significantly higher scores and overall course satisfaction than did students participating in face-to-face courses. The results also indicated that students in hybrid learning classrooms actually felt a stronger sense of community than did students in a traditional classroom setting (Chen & Chiou, 2014).

While one must make many allowances for the various emergency situations brought on by the pandemic (and that there is a distinction between emergency remote instruction and true online teaching/learning), there is plenty of evidence to suggest that well-implemented online teaching/learning can truly enhance student learning beyond what might otherwise be accomplished in a fully face-to-face environment.

Some Best Practices in Online Instruction:

Technology-mediated education is making it possible for students to participate in programs, access content, and connect in ways they were previously unable to.  Rather than viewing the Internet as a necessary evil for distance learning that ultimately begets isolated student learning experiences, digital education should, first and foremost, be connective and communal.  This means a professor accustomed to lecture-based learning in a physical classroom will need to consider a new approach in order to prioritize student voice in the learning process.  In an online context, this means there should be dynamic opportunities for students to engage in debate, reflection, collaboration, and peer review (Weigel, 2002).

If educators are going to seriously account for the rich background experiences, varied motivations, and personal agency of their postsecondary learners, they must also take into account the larger “lifewide” learning that takes place within the lives of their students (Peters & Romero, 2019). Student learning at any age is both formal and informal, and what takes place in a formal classroom environment—digital or otherwise—is influenced by informal learning and daily living that takes place outside of it.  If deep learning takes place, a student’s world and daily life should be altered by the creation of new schemas and the learning that has taken place in a formal classroom environment.  In a multicase and multisite study conducted by Mitchell Peters and Marc Romero in 2019, 13 different fully-online graduate programs in Spain, the US, and the UK were examined in order to analyze learning processes across a continuum of contexts (i.e., to understand to what extent learning was used by the student outside of the formal classroom environment).  In this study, certain common pedagogical strategies arose across programs in support of successful student learning and engagement including:

  1. Developing core skills in information literacy and knowledge management,
  2. Community-building through discussion and debate forums,
  3. Making connections between academic study and professional practice,
  4. Connecting micro-scale tasks (like weekly posts) with macro-scale tasks (like a final project), and
  5. Applying professional interests and experiences into course assignments and interest-driven research.

(Peters & Romero, 2019).

In many regards, each of these pedagogical strategies is ultimately teaching students to “learn how to learn” so that the skills they cultivate in the classroom can be applied over and over again elsewhere. This means that, where digital learning is concerned, the most important learning activities aren’t actually taking place in a large, synchronous Zoom meeting or broadcasted lecture series.

On a practical level, educators can also give attention to some of these simple “tricks of the trade” that have been proven to enhance student learning experiences in a virtual classroom:

  1. Communicate often with students to promote a feeling of connectedness
  2. Create ample space for student voice
  3. Take care that a course set-up in a learning management system is intuitively laid out, action oriented, and adaptable to student needs
  4. Give timely feedback and highlight student strengths
  5. Create opportunities for synchronous activities when possible
  6. Be explicit about expected course outcomes

(Vlachopoulos & Makri, 2019)

At the end of the day, learning and schooling no longer have the same direct relationship they had for most of the 20th century; devices and digital libraries allow anyone to have access to information at any time (Wilen, 2009). Schools, teachers, and printed books no longer hold the “keys to the kingdom” as sources of information.  Online education, then, will not function effectively as a large-scale effort to teach students information through a standardized curriculum.  Rather, education must be a highly relevant venture that enables individual students to do something with the virtually endless information and resources they have access to (Wilen, 2009).

Student Agency & Connection Lead to Student Wellbeing:

When considering how to best support student wellbeing in an online learning environment (at every level), it’s important to remember that the student is not a passive entity.  Indeed, the extent to which students are able to exercise agency in their learning can have a significant impact on their academic success, their attitude towards the learning experience, and their social-emotional wellbeing.  In this case, agency can be interpreted as a student’s ability to exercise choice and be meaningfully present and interactive in the online learning environment.

One of the significant benefits of learning management systems and digital classrooms is the existence of a platform through which resources and learning materials can be shared and posted for any length of time.  Thus, students have the ability to review online course materials at their own pace and engage at a rate that makes sense for their individual needs (Park, 2010).  Allowing students the time and space to persist in completing online learning activities can have significant impact on a students’ success in an academic course (Park, 2019).

Additionally, game-based learning activities, opportunities for collaboration in group projects, participation in threaded discussions, and dedicated spaces for students to freely express their views all assist students in taking ownership of their learning and pursuing their learning interests as those interests materialize in—and overlap with—the course content (Vlachopoulos & Makri, 2019).  These are the activities that directly impact student engagement in a course, as well as the likelihood that a student will have a positive attitude towards the learning experience.

For many traditionally-aged students navigating undergraduate studies during the pandemic, the decreased ability to connect socially with peers, faculty, and support staff has had a direct, negative impact on their academic motivation and overall sense of wellbeing (Burke, 2020).  Thus, creating time and space in the digital learning environment for social interaction, open communication, and for students to gain a sense of identity within the virtual classroom is perhaps more important than ever. 

Finally, it’s very much worth mentioning that the extent to which all spheres of life have been impacted by COVID-19—not just the classroom—is unprecedented.  Helping students think of remote learning as an opportunity for growth, one that will have challenges and limitations as well as potential and new kinds of goals that can be achieved, can help them maintain a sense of purpose and direction amidst the chaos (Burke, 2020).  Growth mindset has already been proven to positively impact student learning at all levels—what better time to remind students (and educators) of the opportunities for growth in the present.

References:

Burke, L. (2020, October 27). Moving into the long term. Inside Higher Ed. https://www.insidehighered.com/digital-learning/article/2020/10/27/long-term-online-learning-pandemic-may-impact-students-well

Chen, B. & Chiou, H. (2014). Learning style, sense of community, and learning effectiveness in hybrid learning environment. Interactive Learning Environments, 22(4), 485-496. https://www.tandfonline.com/doi/abs/10.1080/10494820.2012.680971

Dziuban, C., Hartman, J., Moskal, P., Sorg, S., & Truman, B. (2004). Three ALN modalities: an institutional perspective. In J. R. Bourne, & J. C. Moore (Eds.), Elements of quality online education: Into the mainstream (127–148). Sloan Consortium.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Department of Education, Office of Planning, Evaluation and Policy Development. https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf

Park, E., Martin, F., & Lambert, R. (2019). Examining predictive factors for student success in a hybrid learning course. The Quarterly Review of Distance Education 20(2), 11-27.

Peters, M. & Romero, M. (2019) Lifelong learning ecologies in online higher education: Students’ engagement in the continuum between formal and informal learning. British Journal of Educational Technology, 50(4), 1729.

Vlachopoulos, D., & Makri, A. (2019). Online communication and interaction in distance higher education: A framework study of good practice. International Review of Education, 65,605–632. https://doi.org/10.1007/s11159-019-09792-3

Weigel, Van B. (2002) Deep learning for a digital age.  San Francisco, CA: Jossey-Bass.

Wilen, T. (2009). .Edu: Technology and learning environments in higher education. Peter Lang Publishing.

Posted on

Bias in Higher Ed Admissions: Is New Tech Helping or Hurting?

It’s fairly well known that higher education admissions practices have made headlines in recent years, and issues of access and equity have been at the heart of the controversies. In 2019, a highly-publicized admissions scandal known as Operation Varsity Blues revealed conspiracies committed by more than 30 affluent parents, many in the entertainment industry, offering bribes to influence undergraduate admissions decisions at elite California universities.  The scandal was not limited to misguided actions of wealthy, overzealous parents, however, and it included investigations into the coaches and higher education admissions officials who were complicit (Greenspan, 2019). 

Harvard University has also seen its fair share of scandals including a bribery scheme of its own and controversy over racial bias in the admissions process.  In 2019, a group of Harvard students organizing under the title “Students for Fair Admissions” went to court over several core claims:

  1. That Harvard had intentionally discriminated against Asian-Americans
  2. That Harvard had used race as a predominant factor in admissions decisions
  3. That Harvard had used racial balancing and considered the race of applicants without first exhausting race-neutral alternatives.
Demonstrators hold signs in front of a courthouse in Boston, Massachusetts in October 2018, Xinhua/Barcroft Images

In line with the tenants of affirmative action, the court eventually ruled that Harvard could continue considering race in its admissions process in pursuit of a diverse class, and that race had never (illegally) been used to “punish” an Asian-American student in the review process (Hassan, 2019).  Yet regardless of the ruling, Harvard was forced to look long and hard at its admissions processes and to meaningfully consider where implicit bias might be negatively affecting admissions decisions.

Another area of bias that has been identified in the college admissions system nationwide is the use of standardized tests, especially the SAT or ACT for undergraduate admissions and the GRE or GMAT for graduate admissions.  Changes in demand for these tests have only accelerated during the pandemic with many colleges and universities making SAT/ACT or GRE/GMAT scores optional for admission in 2020-2021 (Koenig, 2020).  Research has oft-revealed how racial bias affects test design, assessment, and performance on these standardized exams, thus bringing biased data into the admissions process to begin with (Choi, 2020). 

That said, admissions portfolios without standardized test scores have one less “objective” data point to consider in the admissions process, putting more weight on other more subjective pieces of an application (essays, recommendations, interviews, etc.). Most university admissions processes in the U.S.—both undergraduate and graduate—are human-centered and involve a “holistic review” of application materials (Alvero et al, 2020).  A study by Alvero et al exploring bias in admissions essay reviews found that applicant demographic characteristics (namely gender and household income) were inferred by reviewers with a high level accuracy, opening the door for biased conclusions drawn from the essay within a holistic review system (Alvero et al, 2020).

So the question remains—how do higher education institutions (HEIs) implement equitable, bias-free, admissions processes that guarantee access to all qualified students and prioritize diverse student bodies?  To assist in this worthwhile quest for equity, many HEIs are turning to algorithms and AI to see what they have to offer. 

Lending a Helping Hand

Without the wide recruiting net and public funding that large State institutions enjoy, the search for equitable recruiting/admissions practices and diverse classes may be hardest for small universities (Mintz, 2020). Taylor University—a small, private liberal arts university in Indiana—has turned to the Salesforce Education Cloud (and the AI and algorithmic tools within) for assistance in many aspects of the admissions and recruiting process.  The Education Cloud and other similar platforms “…use games, web tracking and machine learning systems to capture and process more and more student data, then convert qualitative inputs into quantitative outcomes” (Koenig, 2020). 

As a smaller university with limited resources, the Education Cloud helps Taylor’s admissions officers zero-in on the type of applicants they feel are most likely to enroll, and then identify target populations that exhibit similar data sets in other areas of the country based on that data.  Taylor can then strategically and economically make recruiting efforts where they’re—statistically speaking—likely to get the most interest.  With fall 2015 boasting their largest Freshman class ever, Taylor is, in many ways, a success story, and Taylor now uses Education Cloud data services to predict student success outcomes and make decisions about distributing financial aid and scholarships (Pangburn, 2019).

Understandably, admissions officials want to admit students who have the highest likelihood of “succeeding” (i.e. persisting through to graduation).  Noting that the Salesforce AI predictive tools somehow account for bias that may exist in raw data reporting (like “name coding” or zip code bias), companies with products similar to the Education Cloud market fairer, more objective, more scientific ways to predict student success (Koenig, 2020).  As a result, HEIs like Taylor are confidently using these kinds of tools in the admissions process to help counteract biases that grow “situationally” and often unexpectedly from how admissions officers review applicants, including an inconsistent number of reviewers, reviewer exhaustion, personality preferences, etc. (Pangburn, 2019).   Additionally, AI assists with more consistent and comprehensive “background” checks for student data reported on an application (e.g. confirming whether or not a student was really an athlete) (Pangburn, 2019). Findings from the Alvero et al (2020) study mentioned earlier suggested that AI use and data auditing might be useful in informing the review process by checking potential bias in human or computational readings.

Another interesting proposal for the use of tech in the admissions process is the gamification of data points.  Companies like KnackApp are marketing recruitment tools that would have applicants play a game for 10 minutes.  Behind the scenes, algorithms allegedly gather information about users’ “microbehaviors,” such as the types of mistakes they make, whether those mistakes are repeated, the extent to which the player takes experimental paths, how the player is processing information, and the player’s overall potential for learning (Koenig, 2020). The CEO of KnackApp, Guy Halftek, claims that colleges outside the U.S. already use KnackApp in student advising, and the hope is that U.S. colleges will begin using the platform in the admissions process to create gamified assessments that would provide additional data points and measurements for desirable traits that might not otherwise be found in standardized test scores, GPA, or an entrance essay (Koenig, 2020).

Sample screenshot of a KnackApp game, apkpure.com

Regardless of its specific function in the overall process, AI and algorithms are being pitched as a way to make the admissions system more equitable by identifying authentic data points and helping schools reduce unseen human biases that can impact admissions decisions while simultaneously making bias pitfalls more explicit.

What’s The Catch?

Without denying the ways in which technology has offered significant assistance to—and perhaps progress in—the world of HEI admissions, it’s wise to think critically about the function of AI and algorithms and whether or not they are in fact assisting in a quest for equity.

To begin with, there is a persistent concern among digital ethicists that AI and algorithms simply mask and extend preexisting prejudice (Koenig, 2020).  It is dangerous to assume that technology is inherently objective or neutral, since technology is still created or designed by a human with implicit (or explicit) bias (Benjamin, 2019).  As Ruha Benjamin states in the 2019 publication Race After Technology: Abolitionist Tools for the New Jim Code, “…coded inequity makes it easier and faster to produce racist outcomes.” (p. 12)

Some areas of concern with using AI and algorithms in college admissions include:

  1. Large software companies like Salesforce seem to avoid admitting that bias could ever be an underlying issue, and instead seem to market that they’ve “solved” the bias issue (Pangburn, 2019).
  2. Predictive concerns: if future decisions are made on past data, a feedback loop of replicated bias might ensue (Pangburn, 2019).
  3. If, based on data, universities strategically market only to desirable candidates, they’ll likely pay more visits and make more marketing efforts to students in affluent areas and those who are likely to yield more tuition revenue (Pangburn, 2019).
  4. When it comes to “data-based” decision-making, it’s easier to get data for white, upper-middle-class suburban kids, and models (for recruiting goals, student success, and graduation outcomes) end up being built on easier data (Koenig, 2020).
  5. Opportunities for profit maximization are often rebranded as bias minimization, regardless of the extent to which that is accurate (Benjamin, 2019)
  6. Data privacy… (Koenig, 2020)

Finally, there’s always the question of human abilities and “soft skills,” and to what extent those should be modified or replaced by AI in any professional field.  There’s no denying the limitations AI and algorithms face in making appropriate contextual considerations.  For example, how does AI account for a high school or for-profit college that historically participates in grade inflation?  How does AI account for additional challenges faced by a lower income or first-generation student? (Pangburn, 2019)  There are also no guarantees that applicants won’t figure out how to “game” data-based admissions systems down the road by strategically optimizing their own data, and if/when that happens, you can bet that the most educated, wealthiest, highest-resourced students and families will be the ones optimizing that data, therefore replicating a system of bias and inequity that already exists (Pangburn, 2019).

As an admissions official at a small, liberal arts institution, I am well aware of the challenges presented to recruitment and admissions processes in the present and future, and am heartened to consider the possibilities that AI and algorithms might bring to the table, especially regarding efforts towards equitable admissions practices and recruiting more diverse student bodies.  However, echoing the sentiments of Ruha Benjamin in The New Jim Code, I do not believe that technology is inherently neutral, and I do not believe that the use of AI or algorithms are comprehensive solutions for admissions bias.  Higher education officials must proceed carefully, thoughtfully, and with the appropriate amount of skepticism.

References:

Alvero, A.J., Arthurs, N., Antonio, A., Domingue, B., Gebre-Medhin, B., Gieble, S., & Stevens, M. (2020). AI and holistic review: Informing human reading in college admissions from the proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 200–206. Association for Computing Machinery. https://doi.org/10.1145/3375627.3375871

Benjamin, R. (2019).  Race after technology: Abolitionist tools for the New Jim Code. Polity.

Choi, Y.W. (2020, March 31). How to address racial bias in standardized testing. Next Gen Learning. https://www.nextgenlearning.org/articles/racial-bias-standardized-testing

Greenspan, R. (2019, May 15). Lori Loughlin and Felicity Huffman’s college admissions scandal remains ongoing. Here are the latest developments. Time. https://time.com/5549921/college-admissions-bribery-scandal/

Hassan, A. (2019, November 5). 5 takeaways from the Harvard admissions ruling. The New York Times. https://www.nytimes.com/2019/10/02/us/takeaways-harvard-ruling-admissions.html

Koenig, R. (2020, July 10). As colleges move away from the SAT, will algorithms step in? EdSurge. https://www.edsurge.com/news/2020-07-10-as-colleges-move-away-from-the-sat-will-admissions-algorithms-step-in

Mintz, S. (2020, July 13). Equity in college admissions. Inside Higher Ed. https://www.insidehighered.com/blogs/higher-ed-gamma/equity-college-admissions-0

Pangburn, D. (2019, May 17). Schools are using software to help pick who gets in. What could go wrong? Fast Company. https://www.fastcompany.com/90342596/schools-are-quietly-turning-to-ai-to-help-pick-who-gets-in-what-could-go-wrong

Posted on

Digital Wisdom & Circumnavigating “The Algorithm”

In his 2013 essay “From Digital Natives to Digital Wisdom,” author Marc Prensky claims that an important aspect of exercising digital wisdom involves actively seeking out alternative perspectives, and capitalizing on the enhanced access to these perspectives that technology affords. Though I agree that wisdom in any sphere of life is directly associated with actively seeking out and listening to many different voices, I do not think algorithms, data tracking, cookies, and social media feeds necessarily set up the modern internet user for success in this arena, and we often run the risk of being stuck in our own digital echo chambers. 

Let us first consider the Facebook News Feed.  Facebook is the biggest social network on the planet with over 2.7 billion monthly active users worldwide (Clement, 2020).  For the vast majority of users, the Facebook News Feed serves as the home base and primary content organizer that ultimately determines how users interact with the platform in any given instance, including the content they consume or engage with.  That which shows up on a news feed is determined by a complex algorithm, but the end goal of the news feed is to ultimately show the user content that they find meaningful.  Facebook determines this based on a relevance “score.”  The score is given based on past behaviors (like posts, likes, replies, comments and shares on a user’s profile), past engagement with content from certain publishers, and whether or not the content has been shared from within your friend network (Rubin, 2020).  In short, the more a user interacts with the things they like or are interested in, the more they will have the opportunity to engage with that same type of content in the future.

Facebook’s attempt to narrow the scope of what users interact with is not innately bad; after all, it does help regulate the overwhelming amount of content available on the internet and it attempts to make available content meaningful and hyper-relevant to the user.  But this narrowing of scope has resulted in a risky consequence, namely that the algorithm does not inherently help the user see/read/hear alternative perspectives and thus become more digitally wise.  For most users, the algorithm leads to a fairly robust echo chamber wherein the consumer is constantly being exposed to ideas and sources and content that they (probably) already like or ascribe to.  Especially where news content is concerned, it’s a bit of a breeding ground for confirmation bias. 

(GCFLearnFree, 2019)

So my question is this: how do we “beat the algorithm” in digital spaces (both literally and metaphorically speaking) in order to remain mindful of our information sources and consider the underlying assumptions behind what we consume? How do we self-identify potential echo chambers and intentionally seek out alternative perspectives?

I believe the answer lies (at least partially) in media literacy education. According to Hobbs (2010), media literacy is a subset of digital literacy skills involving:

  1. the ability to access information by locating and sharing materials and comprehending information and ideas
  2. the ability to create content in a variety of forms, making use of digital tools and technologies;
  3. the ability to reflect on one’s own conduct and communication by applying social responsibility and ethical principles;
  4. the ability to take social action by working individually and collaboratively to share knowledge and solve problems as a member of a community;
  5. the ability to analyze messages in a variety of forms by identifying the author, purpose, and point of view and evaluating the quality and credibility of the content.

In a study conducted with 400 American high school students, findings showed that students who participated in a media literacy program had substantially higher levels of media knowledge and news/advertising analysis skills than other students (Martens & Hobbs, 2015).  Perhaps more importantly, information-seeking motives, media knowledge, and news analysis skills independently contributed to adolescents’ proclivity towards civic engagement (Martens & Hobbs, 2015), and civic engagement naturally requires dialogue with others within and outside of an individual’s immediate circle.  In other words, the more students were able to critically consider the content they were consuming and the motives behind why they were consuming it, the more they wanted to engage with alternative perspectives and be active, responsible, productive members of a larger community.

Understanding how the Facebook algorithm works is one form of media literacy education and it can certainly go a long way in helping users of that particular platform identify and avoid echo chambers therein.  However, echo chambers can exist outside of the Facebook algorithm to the extent that any given individual fails to seek out opinion-challenging information.  Therefore, in an attempt to lean into media literacy and, by extension, civic engagement, here are three simple but meaningful tips that the digitally wise might find useful:

  1. Habitually check multiple news sources; this is the only surefire way to ensure you’re getting complete information with the maximum amount of objectivity.
  2. Intentionally reach out and interact with people of different perspectives, both on and offline; take care to discuss new ideas with facts, patience, and respect.
  3. Be aware of your own biases; wanting something to be true doesn’t make it factual. (GCF Global, 2020)

These “tricks of the trade” are not revolutionary, nor do they find their origins with the dawning the internet, yet these are the very practices that have, perhaps, become more difficult to actively employ in digital space.  Consequently, reminders about the simple things never hurt.  Simple concepts aren’t necessarily simple to enact.  The passive internet user is the one most likely to get caught in an echo chamber; the digitally-wise will make consistent efforts to challenge their own thinking and intentionally seek out alternative voices, even if it takes a little bit more elbow grease to do it.

References:

Clement, J. (2020). Number of monthly active Facebook users worldwide as of 2nd quarter 2020. Statista. https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/    

GCF Global. (2020, October 8). What is an echo chamber? Digital Media Literacy. https://edu.gcfglobal.org/en/digital-media-literacy/what-is-an-echo-chamber/1/

GCFLearnFree. (2019, June 18). What is an echo chamber? YouTube. https://www.youtube.com/watch?v=Se20RoB331w&feature=emb_logo

Hobbs, R. (2010). Digital and media literacy: A plan of action. The Aspen Institute Communications and Society Program & the John S. and James L. Knight Foundation. https://knightfoundation.org/reports/digital-and-media-literacy-plan-action/

Martens, H. & Hobbs, R. (2015). How media literacy supports civic engagement in a digital age.  Atlantic Journal of Communication, 23, 120–137.

Prensky, M. (2013). From digital natives to digital wisdom: Hopeful essays for 21st century learning. Corwin, 201-215.

Rubin, C. (2020). 10 ways to beat the Facebook algorithm in 2020. UseProof. https://blog.useproof.com/facebook-algorithm

Posted on

An Ethic of Authenticity in Digital Media & Communications

As someone who is currently working in a recruiting/marketing role in higher education, I am consistently involved in the media representation and strategic communications produced on behalf of the programs and organization I work with/for.  I also have to make choices about how to engage in interactive technological communications (e-mails, video conferencing) and represent myself in digitally-mediated relationships as I recruit and advise prospective students. As has been the case for so many others, COVID-19 has only increased the amount of work and communication I do in the digital space.

Ethical values that are very important to me in my professional context, and as a digital citizen advocate, are authenticity and transparency, especially as they relate to media representation and digitally-mediated relationships.  Higher education institutions adopt and implement new information and communication technologies (ICTs) frequently, but little time is given for critical reflection on how they are being used (or how they ought to be used) by the students, faculty, and staff who engage with them (Paulus et al., 2019). So, in an effort to think critically, I’d like to explore what authenticity and transparency look like in media representation and online presence for a large organizational and, more specifically, for an individual representative of that organization.

Digital media and ICTs complicate meaningful pursuits of authenticity from a public relations standpoint; these technology-mediated realms of human interaction challenge what we see as authentic and make it harder to tell the difference between what is “real” and what is “fake” (Molleda, 2010).  One need look no further than “reality” TV, social media personas, and journalistic integrity in the era of “fake news” to understand that not all claims of authenticity in media are substantive.

Additionally, an exchange of information—and by extension the authenticity of that information—is just that: an exchange.  The presentation of information, authentic or otherwise, isn’t unidirectional; all actors have the potential to influence one another and the flow of information (Chin-Fook & Simmonds, 2011). Thus, the power behind authenticity claims does not rest solely with the creator or presenter of the content, but also with those who will be interpreting and negotiating meaning from it.  That which is considered authentic by stakeholders will be socially and culturally influenced (Molleda, 2010).

But perhaps we must first further explore what the ethic of authenticity is before attempting to examine what it looks like in practice in digital spaces, especially from a marketing and communications lens.  In a comprehensive literature review, Molleda (2010) found that several pervasive themes, definitions, and perceptions of authenticity consistently surfaced across a variety of disciplines.  Taken as a whole, Molleda (2010) asserts that these claims may be used to “index” or measure authenticity to the extent that they are present in any given communication or media representation.  Some of these key aspects of authenticity include:

  1. Being “true to self” and stated core values
  2. Maintaining the essence of the original (form, idea, design, product, service, etc.)
  3. Living up to others’ expectations and needs (e.g. delivering on promises)
  4. Being original and thoughtfully created vs. mass produced
  5. Existing beyond profit-making or corporate/organizational gains
  6. Deriving from true human experience

I have italicized the last of these markers of authenticity because it seems the most comprehensive—and perhaps the most important—marker in a digital space. Granted, certain aspects of human experience are not easily replicated in online media, including a grounded sense of time/place and sensory cues like smell, physical touch, or visual elements outside of a screen that would otherwise add context (McGregor, 2013). Consider the idyllic social media picture that fails to incorporate the “mess” of real life that we might otherwise see just outside the frame.  What can be conveyed in digital media and communications, however, are human stories and that which directly flows out of those experiences.  As Molleda (2010) says, “The search for, and identification of, real stories and people within organizations…is part of the critical job that [public relations] practitioners must perform” (p. 224).

In my context, that means that communication/marketing efforts grounded in student narrative and in my own relevant experiences will be organically authentic. Photographs, testimonials, and statistics derived from current student cohorts and recent graduates aren’t just helpful tools for marketing, they actually carry ethical weight.  They will also likely be the most effective way to engage future students in a sincere way that is also received as authentic.

Additionally, a good test for authenticity is whether or not I—as an individual representative of my organization—am willing to “openly, publicly and personally be identified as the persuader in a particular circumstance” (Baker & Martinson, 2002, p.17).  In other words, in my sphere of influence with media representation and communications, it’s important to stop and ask myself: am I willing to be personally associated with this content (Molleda, 2010)? There’s no doubt that in the digital space there are often blurred lines between personal and professional online identities, so it’s worthwhile to consider that professional actions and communications online might easily have personal consequences (and vice versa), both now and in the future.  

Finally, and perhaps anecdotally, if we assume that true human experience lies at the heart of authenticity in the digital realm, there must be room for “customers” to decide whether or not the offerings (in this case, graduate programs) are indeed best fit for their needs. This goes against the nature of higher educational institutions that are perpetually competing for student tuition dollars, but if practicing authenticity includes a willingness to look beyond profit-making and organizational gains, then media representation and student interactions will allow students the space to decide what’s best for them, even if that means going somewhere else.  If it becomes clear that the “product” I’m associated with can’t appropriately serve the aspirations and expectations of the interested party, then an ethic of authenticity would demand that I communicate as much to the prospect.  This also requires attention to any “lie of omission” that might exist wherever a transfer of information takes place, a crime that is much easier to commit in a digital space.  An ethic of authenticity goes beyond any kind of plan or strategic marketing campaign; authenticity is about presenting the essence of what already exists and whether (or not) it has the ability to live up to its own and others’ expectations and needs (Molleda, 2010).

Molleda (2010) concludes that consistency between “the genuine nature of organizational offerings and their communication is crucial to overcome the eroding confidence in major social institutions” (p. 233). I for one hope to continue embodying an ethic of authenticity in my professional work—in digital spaces and otherwise—in  order to set the stage for that consistency and to bolster societal confidence in at least one higher education institution.

References

Baker, S. & Martinson, D.L. (2002). Out of the red-light district: five principles for ethically proactive public relations. Public Relations Quarterly, (47)3, 15-19.

Chin-Fook, L. & Simmonds, H. (2011). Redefining gatekeeping theory for a digital age. McMaster Journal of Communications, 8, 7-34. https://journals.mcmaster.ca/mjc/article/view/259

Molleda, J. (2010). Authenticity and the construct’s dimensions in public relations and communication research. Journal of Communication Management,14(3), 223-236. http://dx.doi.org.ezproxy.spu.edu/10.1108/13632541011064508 

McGregor, K.M. (2013). Defining the ‘authentic’: Identity, self-presentation and gender in Web 2.0 networked social media. [Doctoral dissertation, University of Edinburgh]. Edinburgh Research Archive. http://hdl.handle.net/1842/16240

Paulus, M.J., Baker, B.D., & Langford, M.D. (2019). A framework for digital wisdom in higher education. Christian Scholar’s Review, 49(1), 41-61. http://works.bepress.com/michael_paulus/68/

Posted on

A Few Best Practices for Online Learning & Adoption in Higher Education

Though the digital age may not actually be changing a student’s capacity to learn, it’s certainly changing how students access content and participate in learning environments. Digital technology thoroughly transforms the way in which we create, manage, transfer, and apply knowledge (Duderstadt, Atkins, & Van Houweling, 2002). Unsurprisingly, it’s also changing how educators teach, particularly with technology-mediated instruction in higher education. The demand for online instruction is on the rise.  In the United States alone, the number of higher education students enrolled in online courses increased by 21% between fall 2008 and fall 2009, and the rate of increase has only grown in recent years, both nationally and globally (Bolliger & Inan, 2012).  Of course, the COVID-19 pandemic of 2020 has also necessitated a radical—though in some cases temporary—shift to online learning modalities at all educational levels across the globe.

Fortunately, there’s evidence to support that digital education incorporation can enhance pedagogy and improve overall student performance at the college level.  An extensive, multi-year case study conducted at the University of Central Florida showed that student success in blended programs (success being defined as achieving a C- grade or higher) actually exceeded the success rates of students in either fully online or fully face-to-face programs (Dziuban, C., Hartman, J., Moskal, P., Sorg, S., & Truman, B., 2004).

In the switch to online teaching and learning, a clear challenge is presented: teaching faculty are faced with a need to move their programs and classes into online/flexible learning formats, regardless of their discipline or their expertise/ability to do so.  It is not uncommon for teachers, no matter the level at which they teach, to be asked to implement something new in their classroom without sufficient support, professional development, or resources to make the implementation successful.  The need for appropriate training becomes that much more pressing when educators are asked to engage with an entirely different instruction medium from that which they are accustomed to.  In the case of blended or online learning, many faculty will need to develop completely new technological and/or pedagogical skills.  While a number of scholars have conducted investigations into the effectiveness of blended or online learning, very few have provided guidance for adoption at the institutional level (Porter, Graham, Spring, & Welch, 2014). 

Far from being a comprehensive guide, this post seeks to explore a few major themes and best practices for online learning in postsecondary education which may prove helpful for teaching professionals and higher education institutions heading into an otherwise unfamiliar world of digital education.

Create a Learning Community:

Digital education is made possible by computers and the internet.  In the age of the Internet, the computer is ultimately used most to provide connection, whether that be through social media, e-commerce, gaming, publications, or education (Weigel, 2002).  Technology-mediated education is making it possible for students to participate in programs, access content, and connect in ways they were previously unable to.  Rather than viewing the Internet as a necessary evil for distance learning that ultimately begets isolated student learning experiences, digital education should, first and foremost, be connective and communal.  This means a professor accustomed to lecture-based learning in a physical classroom may need to consider a new approach in order to make space for student voice in the learning process.  In an online context, this means there should be dynamic opportunities for students to engage in debate, reflection, collaboration, and peer review (Weigel, 2002).

Beyond Information Transfer:

Learning and schooling no longer have the same direct relationship they had for most of the 20th century; devices and digital libraries allow anyone to have access to information at any time (Wilen, 2009). Schools, teachers, and even books no longer hold the “keys to the kingdom” as sources of information.  Higher education, then, will not function effectively as a large-scale effort to teach students information through a standardized curriculum.  Rather, education must be a highly relevant venture that enables individual students to do something with the virtually endless information and resources they have access to (Wilen, 2009).

Relevance:

If university instructors are going to seriously account for the rich background experiences, varied motivations, and personal agency of their postsecondary students, they must also take into account the larger “lifewide” learning that takes place within the life of most college students (Peters & Romero, 2019). Student learning at any age is both formal and informal, and what takes place in a formal classroom environment is influenced by informal learning and daily living that takes place outside of it.  Likewise, if deep learning takes place, a student’s world and daily life should be altered by the creation of new schemas and the learning that has taken place in a formal classroom environment. 

In a multicase and multisite study conducted by Mitchell Peters and Marc Romero in 2019, 13 different fully-online graduate programs in Spain, the US, and the UK were examined in order to analyze learning processes across a continuum of contexts (i.e., to understand to what extent learning was used by the student outside of the formal classroom environment).  Certain common pedagogical strategies arose across programs in support of successful student learning and engagement including: developing core skills in information literacy and knowledge management, community-building through discussion and debate forums, making connections between academic study and professional practice, connecting micro-scale tasks (like weekly posts) with macro-scale tasks (like a final project), and applying professional interests and experiences into course assignments and interest-driven research (Peters & Romero, 2019).  In many regards, each of these pedagogical strategies is ultimately teaching students to “learn how to learn” so that the skills they cultivate in the classroom can be applied over and over again elsewhere.

Professional Development:

Still there remains the question of implementation.  In order for the mature adoption of digital education to take place, faculty need to be given time and training to help them develop new technological and pedagogical skills.  If an institution fails to provide sufficient opportunities for professional development, many faculty members will likely fail to fully embrace the shift to an online format, and will instead replicate their conventional teaching methods in a manner that isn’t compatible with effective online instruction (Porter, et al., 2014).  If higher education institutions are committed to delivering high quality instruction in all contexts, it will be important for administrators to retain qualified instructors who are motivated to teach online and who are satisfied with teaching online (Bolliger, Inan, & Wasilik, 2014).

 In a 2012-2013 survey of 11 higher education institutions reporting on their implementation of blended learning programs, Wendy Porter et al found that every university surveyed provided at least some measure of professional development to support faculty in the transition.  Each university had their own customized approach, but the fact that developmental support was prioritized in some regard remained consistent across all of the institutions in the survey.  Strategies used for professional development in digital learning included presentations, seminars, webinars, live workshops, orientations, boot camps, instructor certification programs for online teaching, course redesign classes, and self-paced training programs (Porter et al., 2014).

Digital Literacy:

Digital literacy among higher education faculty can’t be taken for granted.  A recent Action Research study aimed at exploring the digital capacity and capability of higher education practitioners found that, though the self-reported digital capability of an individual may be relatively high, it did not necessarily relate to the quality of their technical skills in relation to their jobs (Podorova et al., 2019).  Survey results from the study also showed that the majority of practitioners (41 higher education professors in Australia) were self-taught in the skills they did possess, receiving very little formal training or support from their employer, even with technology devices and tools directly pertaining to teaching and assessment (Podorova et al., 2019).  Though this data relates to a specific case study, it is not difficult to imagine that higher education faculty in institutions all over the world might report similar experiences.  If faculty aren’t given sufficient technological support and training, they will be less satisfied in their work and, ultimately, the student experience will suffer (Bolliger, et al., 2014).

Institutional Adoption:

In addition to providing sufficient technological or pedagogical resources, it is important for university administrators to communicate the purpose for online course adaptation.  In a later study conducted by Wendy Porter and Charles Graham in 2016, research indicated that higher education faculty more readily pursued effective adoption strategies when they were in alignment with the institution’s administrators and the stated purpose for doing so (Porter & Graham, 2016). If faculty members are, in essence, adult learners being asked to acquire new skills, it is essential to take their own motivations for learning into account.  Additionally, sharing data and course feedback internally from early-adopters to online instruction can go a long way in helping reticent faculty feel ready to approach online learning (Porter & Graham, 2016).  Institutional support is cited frequently in literature pertaining to faculty satisfaction in higher education. In the domain of online learning, institutional support looks like: providing adequate release time to prepare for online courses, fair compensation, and giving faculty sufficient tools, training, and reliable technical support (Bolliger et al., 2014).

One effective approach to professional development for online learning places professors in the seat of the student.  At Hawaii’s Kapi’olani Community College on the island of Oahu, Instructional Designer Helen Torigoe was charged with training faculty in the process of converting courses for online delivery.   In response, Torigoe created the Teaching Online Prep Program (TOPP) (Schauffhauser, 2019). In TOPP, faculty participate in an online course model as a student, using their own first-hand experience to inform their course creation.  As they participate in the course, faculty are able to use the technology that they will be in charge of as an instructor (programs like Zoom, Padlet, Flipgrid, Adobe Spark, Loom, and Screencast-O-Matic), gaining comfort and ease with the tools and increasing their overall digital literacy.  Faculty also get a comprehensive sense for the student experience while concurrently creating an actual course template and receiving guidance and support from the TOPP course coordinator.  Such training is mandatory for anybody teaching online for the first time at Kapi’olani Community College. A “Recharge” workshop has also been created to help faculty engage in continued learning for best practice in digital education, ensuring that faculty do not become static in their teaching methods and are consistently exposed to new tools and strategies for digital education (Schauffhauser, 2019).  Institutions that participate in online education need to provide adequate training in both pedagogical issues and technology-related skills for their faculty, not only when developing and teaching online courses for the first time, but as an ongoing priority in faculty professional development (Bolliger et al., 2014).

Summary:     

The number of graduate courses and programs that must be offered in an online format is increasing in many higher education environments.  Effective online educators will acknowledge the unique needs of their postsecondary learners: that their students need to have their background experiences and context utilized in the learning process, that their learning needs to be relevant to their life and work, and that their learning needs to be providing them with actionable skills and learning strategies that ultimately change how they interact with their world.  Effective online learning will also provide ample space for student connection and active participation.  This means there should be dynamic opportunities for students to engage in debate, reflection, collaboration, and peer review (Weigel, 2002).  Additionally, online learning ought to be a highly relevant venture that enables individual students to do something with the virtually endless information and resources they have access to (Wilen, 2009).  Yet in order for the mature adoption of digital education to take place, faculty need to be given time and training to help them develop new technological and pedagogical skills.  This training needs to happen with initial adoption and as an ongoing venture.  One example of highly effective faculty professional development can be found in Instructional Designer Helen Torigoe’s Teaching Online Prep Program (TOPP) (Schaffhauser, 2019).  In this program the instructors become the students as they familiarize themselves with a new learning system, create a customized course template, and get feedback and support from knowledgeable online educators.  In short, well-equipped, well-trained, and well-supported graduate faculty are fertile ground for effective online education.

References

Bolliger, D. U., Inan, F. A., & Wasilik, O. (2014). Development and validation of the online instructor satisfaction measure (OISM). Educational Technology Society, 17(2), 183–195.

Duderstadt, J., Atkins, D., Van Houweling, D. (2002). Higher education in the digital age: Technology issues and strategies for American colleges and universities. Praeger Publishers.

Dziuban, C., Hartman, J., Moskal, P., Sorg, S., & Truman, B. (2004). Three ALN modalities: An institutional perspective. In J. R. Bourne, & J. C. Moore (Eds.), Elements of quality online education: Into the mainstream (127–148). Sloan Consortium.

Peters, M. & Romero, M. (2019) Lifelong learning ecologies in online higher education: Students’ engagement in the continuum between formal and informal learning. British Journal of Educational Technology, 50(4), 1729.

Podorova, A., Irvine, S., Kilmister, M., Hewison, R., Janssen, A., Speziali, A., …McAlinden, M. (2019). An important, but neglected aspect of learning assistance in higher education: Exploring the digital learning capacity of academic language and learning practitioners. Journal of University Teaching & Learning Practice, 16(4), 1-21.

Porter, W., & Graham, C. (2016). Institutional drivers and barriers to faculty adoption of blended learning in higher education. British Journal of Educational Technology, 47(4), 748-762.

Porter, W., Graham, C., Spring, K., & Welch, K. (2014). Blended learning in higher education: Institutional adoption and implementation. Computers & Education, 75, 185-195.

Schaffhauser, D.  (2019). Improving online teaching through training and support. Campus Technology. https://campustechnology.com/articles/2019/10/30/improving-online-teaching-through-training-and-support.aspx

Weigel, V.B. (2002) Deep learning for a digital age. Jossey-Bass.

Wilen, T. (2009). .Edu: Technology and learning environments in higher education. Peter Lang Publishing.

css.php