Leveraging Digital Tools for Instruction Outside the Classroom: Community Engagement Project, EDTC 6102

It’s been a wonderful opportunity to invest time and energy into a project which ultimately helps me do my job better.  Though I am not currently a classroom teacher and do not have typical instructional responsibilities in my day to day work, I do constantly convey important information about the WA State teacher certification process to prospective educators, a process which can often feel overwhelming and convoluted to many would-be career changers. I feel confident that I’ve put together a blueprint for a meaningful, engaging informational session which will help students navigate the first steps of the certification process with confidence and clarity, ultimately helping them discern for themselves if becoming a teacher is the right step for them professionally at this time, and if so, how to make that a reality. Not only that, I’ve been able to think creatively about how to leverage digital tools to make the session interactive, student-centered, and practically useful to those who attend.

Lesson Plan for 60 Minute Information Session

This lesson plan is intended for a Group of 10-20 prospective graduate students using a virtual teleconference platform like Zoom, Teams, Google Meet, etc.

Note: some hyperlinks may not be accessible to all due to permissions settings

Introduction 
10 min.
Students will be notified of my intention to record the session and their associated rights (turning off video, etc.).

Introduce Self and Learning Objectives of Info Session:
Objective 1: learn how someone becomes a teacher in WA State and determine personal readiness to begin the process.
Objective 2: learn what program options are available at SPU and which program is best-fit for personal context
Objective 3: learn what steps to take next with an application to a teacher certification program

10 Signs That You Should Become a Teacher, opening reflection video
Interactive Presentation
20 min.
Google Slide Deck
Students will be provided with access to the Google Slide Deck in advance of the information session so that they may conduct research ahead of time or follow along independently, clicking on hyperlinks, etc. in their own browser window. I will also use it to structure the presentation of information in the session.  For those who do not choose to follow along independently, hyperlinks for interactive elements will be provided directly in the session chat.

Within the slide deck, students will be introduced to SPU’s various graduate teacher certification program options.Students will be given the opportunity to stop and reflect on what feels like their best-fit program halfway through, before new information about the application process is introduced.  They will also be given the opportunity to ask clarifying questions at this point via Jamboard.

Students will then be given detailed information about application requirements and due dates, including specific information about the endorsement verification process.  This is also a time where I intend to help students understand and navigate the various information systems which they will have to engage with throughout the certification and application process (online application, standardized tests, etc), and to what extent they’ll be expected to provide personal data in digital spaces.
Formative Assessment 10 min.Prospective students will then have the opportunity to review and test their understanding of the material via a brief, 15-question Kahoot Quiz.  This will also serve as a formative assessment tool for me, the instructor, and may help point out areas that need further clarification. There will be time to pause and address these areas while going through the Kahoot Quiz.
Performance Task 
10 min.
Students will then have the opportunity to curate a personal To Do List outlining their next steps towards an application (and thus, towards becoming a teacher).  This is a performance task that helps students indicate their understanding of the material covered in the information session, but it is also meant to be a practical, relevant takeaway for each attendee.

Students will be able to make a copy of this Google Doc Template which contains a scaffolded “word bank” of application requirements.  Students will be able to copy/paste from the word bank in order to create their own, personalized To Do List, paying special attention to their specific program needs, endorsement requirements, and chronological order (i.e. which items need attention first). I will also provide the Google Doc Template in an alternate format (i.e. Word document) for any students that need it after the session. 
Self-Assessment & Reflection
10+ min.
Shortly after providing students with the Google Doc Link, I will provide a link to the final Sticky Note Q & A w/ Jamboard so that students may ask any needed questions while they construct without interrupting the thought processes of others in the session.  They may also choose to drop questions privately to me in the chat depending on the immediacy of the need and/or group appeal of their question. 

After the allotted 10 minutes passes for list construction, I’ll also offer a final few minutes for students to review their lists and ask final questions that need resolving on the Jamboard, OR live in the video conference, time permitting. The session will be recorded and the recording will be provided to students after the information session via email. This allows students to go back and review as needed.

Throughout this session, students will have the opportunity to demonstrate their understanding through application and self-knowledge.

  • Application: as students create their own, personally curated “To Do List” they will be able to apply their understanding of the session material by creating a useful tool that will guide them moving forward.  This includes discerning which information is most relevant to their particular context.  Students will be able to effectively navigate the various information systems which they will have to engage with throughout the certification and application process, especially in regards to the information they provide during the application process.  This also brings to mind the fact that students will literally apply to a program as part of their next steps towards becoming a teacher.
  • Self-Knowledge: students will be invited to reflect on their motivations to become a teacher, whether now is the time to take steps towards becoming a teacher, as well as what kind of program would be best suited for their needs. There will also be ample time for students to grapple with what they do not know, or what is confusing for them in this process.  The decisions they make moving forward will be rooted in the self-knowledge acquired from this session.

I do believe that the most helpful reflections on this “lesson plan” will come after I’ve had the opportunity to put it into action for the first time in a professional setting, likely in Fall of 2021. That said, One area for potential improvement that I can already identify is the curated “To Do List” platform.  Though I found some potential tools that I was interested in which might be a bit sleeker/less cumbersome than using a Google Doc, the ones I came across were not open access or would require a full account set-up in order to use them. This wouldn’t translate well to the timing and context of this particular lesson, nor the student audience (i.e. prospective students attending an information session, not students enrolled in a class).  Thus, for now, I have the Google Doc format as a bit of a place-holder.  I’m quite open to tweaking this section of my lesson in favor of a better tool later on.

In summary, this particular project was a wonderful exercise in thinking about learning and instruction on a macro level and the many ways they take place outside of a formal classroom environment. Digital tools may be leveraged in a myriad of ways to help us do our jobs better, and this was an opportunity for me to think creatively about how to bring that home in my own context. I look forward to using this session format in the next recruiting cycle!

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  

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.

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

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

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.

An ethical value that is very important to me in my professional context and as a digital citizen advocate is authenticity and transparency, especially as it relates to media representation and digitally-mediated relationships.  Higher education institutions often 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/