21st Century Skills in the Higher Education Classroom

The term “21st Century Skills” has been referenced frequently in education circles for over a decade.  Though the educational philosophies and political/economic motivations undergirding these skills originated well before the dawn of the 21st century, the list that coalesced into the 21st Century Skills we recognize in American education today gained prominence with educational initiatives like the Partnership for 21st Century Skills (P21) Framework for education (2002) and the Common Core State Standards (2010).  21st Century Skills have been discussed ubiquitously over the years, but generally speaking, 21st Century Skills are “…the knowledge, life skills, career skills, habits, and traits that are critically important to student success in today’s world…” (Buckle, n.d.).  The P21 Framework for 21st Century Learning categorizes 21st Century Skills this way: 

  • Learning Skills: Also known as the “Four Cs”–critical thinking, communication, collaboration, and creativity. 
  • Life Skills: Flexibility, initiative, social skills, productivity, leadership 
  • Literacy Skills: Information literacy, media literacy, technology literacy 

(Buckle, n.d.) 

Much effort has gone into applying these skills to K-12 education curriculum and standards.  Indeed, the Common Core State Standards are excellent examples of just such an effort.  Another set of standards, the International Society for Technology in Education (ISTE) Standards for students, educators, coaches, and educational leaders, are closely tied to the successful integration of 21st Century Skills in classrooms and teacher preparation programs, especially where the last bullet point listed above is concerned.  According to the ISTE website, their standards for technology use and integration have been adopted in all 50 states and in a number of countries across the globe.  They exist as valuable resources and guidance for educators trying to understand how to best integrate technology in their classroom, no matter the age or content. 

A gap exists, however, between K-12 and higher education, such that the standardization of, well…. anything really…in postsecondary education becomes tricky.  Higher education instructors aren’t required to go through any kind of teacher preparation program before they begin teaching, they merely need to be experts in their discipline, and perhaps productive researchers.  Being a good teacher is often just a bonus in higher ed. Thus, credential requirements and State standards for educators don’t apply in higher ed the same way they would in K-12 education or in teacher prep programs.  Neither are there any kind of central, cohesive, discipline-neutral, nationwide standards that define what it means to earn a degree in a particular field and possess the “21st Century Skills” necessary for future success, either at the undergraduate or graduate level.  There may be accreditation guidelines, field-specific certifications, practicums, or comprehensive exams which help structure higher education curricula, but because of the vastly differing needs/demand of higher education disciplines, postsecondary instructors have a great deal of autonomy in their approach to teaching and learning, for better and for worse. 

Technology integration in the higher ed classroom, then, is no exception.  Returning to the concept of 21st Century Skills, high school graduates hardly arrive at higher education institutions in possession of all the 21st Century Skills they need to thrive in the workplace or in society.  If they did, they might be advised to skip college and head straight into the work force. So what kind of 21st Century Skill development is expected of students in postsecondary education?  Are these any different than those expected of students in K-12?  And perhaps most importantly, where should higher education instructors and coaches look for guidance? 

The 21st Century has brought with it a “new learning paradigm” (Kivunja, 2014).  In order for higher education instructors to be effective within this new paradigm, they must first be willing to move away from a teacher-directed model wherein the main objective in a course is transferring content knowledge.  Instead, the slow-moving machine that is higher education must prioritize student-centered learning that promotes an active exchange of ideas, the acquisition of new skills, and the application of those skills to solve problems in real-world situations (Kivunja, 2014).  Roger Brooks of Connecticut College shared his own, similar ideas about 21st Century teaching/learning in higher education in his 2013 Tedx presentation: 

(minutes 10:10-12:00 are most pertinent to this discussion) 

But where to begin?  If a higher education instructor or instructional coach/designer are on board with this paradigm, what are some practical suggestions for how to start transforming teaching/learning in the classroom now?  Perhaps recognizing that there is a gap in resources specifically aimed at supporting instructor training and best practices for student-centered, 21st Century teaching/learning in higher ed, Germaine et al (2016) offer some practical suggestions for integrating the four C’s of 21st Century Learning Skills into postsecondary teaching/learning: 

  1. Critical Thinking/Problem Solving: 
  • Allow student choice to determine areas of research 
  • Encourage students to closely examine values/ideas/concepts and weigh them against their own personal values/ideas/concepts 
  • Provide space for intellectual autonomy 
  1. Communication: 
  • Assign group projects which require successful interpersonal communication to achieve a common goal 
  • Leverage technology to have students communicate ideas in nonverbal ways (graphics, visuals, multi-media) 
  • Create space to consider how communication strategies might differ in global contexts 
  • Review, evaluate, and critique communication efforts 
  1. Collaboration: 
  • Utilize online professional learning communities in which students engage in group problem solving and feedback 
  • Consider how the use of social media, blogs, and discussion forums can be best used to promote student interaction 
  • Use assignments/projects which ask students to connect with those outside their peer group and even the institution 
  1. Creativity/Innovation: 
  • Establish assignments or projects with a clear objective or end goal but with real freedom in deciding how that objective or end goal will be met. 
  • Use concept mapping to help students create unique representations of abstract concepts 
  • Have students “write their own exam” and have them reflect their understanding of a concept by creating their own assessment 

This list of suggestions is hardly exhaustive, but it’s heartening to be reminded of the ways 21st Century Skills can be implemented with versatility and without feeling limited by the parameters of a specific discipline.  It’s also proof that 21st Century Skills, no matter the lists, standards, or frameworks in which they appear (and there are many), are indeed essential to the postsecondary classroom and should not be relegated to the concerns of K-12 teachers and administrators.  Whether higher education instructors need to be pointed to the ISTE standards, the P21 Framework, or some other list of 21st Century Skills, the skills themselves are relevant to learning and student success from preschool to graduate school.  Perhaps what we need is more higher education instructors speaking out about successes in their classrooms and disciplines, inspiring others to think critically and creatively about how 21st Century teaching/learning could be brought to life in their own contexts.  

References: 

Brooks, R. (2013, May 26). Rethinking Higher Education for the 21st Century: Roger Brooks at TEDxConnecticutCollege.  Youtube. https://www.youtube.com/watch?v=4avr9l6DTtM 

Buckle, J. (n.d.). A comprehensive guide to 21st Century Skills. Panorama Education. https://www.panoramaed.com/blog/comprehensive-guide-21st-century-skills 

Germaine, R., Richards, J., Koeller, M., Schubert-Irastorza, C. (2016). Purposeful use of 21st Century Skill sin higher education. Journal of Research in Innovative Teaching, 9(1), p.19-29. https://www.nu.edu/wp-content/uploads/2018/11/journal-of-research-in-innovative-teaching-volume-9.pdf#page=27 

Kivunja, C. (2014). Innovative pedagogies in higher education to become effective teachers of 21st Century Skills: Unpacking the learning and innovations skills domain of the new learning paradigm. International Journal of Higher Education3(4) p37-48. https://eric.ed.gov/?id=EJ1067585 

Shoology (2018, November 19). What are the ISTE Standards for Teachers and why are they relevant? Schoology Exchange. https://www.schoology.com/blog/understanding-iste-standards-teachers 

Exemplars of Computational Thinking in Higher Education Classrooms

Though the concepts and theory behind computational thinking (CT) have been around for decades in the realms of computer science and engineering, it is widely acknowledged that Jeanette Wing’s 2006 publication on computational thinking laid the groundwork for CT’s popularity and integration in 21st century education theory.  Wing (2006) suggested that CT might be considered essential to all human endeavors as it is a distillation of a way that we naturally approach solving problems, managing our daily lives, and communicating and interacting with people.  It need not be relegated only to the STEM fields and computer science majors, because CT is not about getting humans to think like computers.  Rather, CT harnesses the natural outpouring of human cleverness, creativity, and problem solving that laid the foundations for the field of computer science in the first place (Wing, 2006). CT is about “…solving problems, designing systems, and understanding human behavior” by drawing on, and leveraging, the concepts fundamental to computer science (Wing, 2006, p. 33).

Though academics continue to debate an authoritative definition for CT, certain common themes are generally accepted characterizations of CT across the board.  These characteristics include:

  • Abstraction — thinking through abstract concepts and ill-defined problems, at times breaking them into smaller, digestible pieces, in order to move towards a more concrete, real-world solution (Wing, 2006).
  • Pattern Recognition —  recognizing useful patterns in data, filtering out the characteristics of patterns that aren’t needed, focusing on those that are (Wing, 2006).
  • Algorithmic Thinking — curating a list of steps that can be followed to solve a problem (Lyon & Magana, 2020).
  • Creative Problem Solving — developing a unique, context-based solution that is  considered original, valuable, and useful (Romero et.al., 2017).
  • Evaluating Solutions — considering the efficacy of a proposed solution to a problem, perhaps making considerations for factors like efficiency and resource consumption (Lyon & Magana, 2020).
Image sourced from https://koneilleci201.wordpress.ncsu.edu/2020/01/28/computational-thinking/

These facets of CT and the related skills are all integral parts of a 21st century education at all levels, including K-12 and postsecondary.  Indeed, “…computational sciences have been deemed essential to maintaining national competitiveness in the workplace and national security.” (Lyon & Magana, 2020, p. 1174)  For these reasons, the fundamentals of CT have been championed in education theory over the last decade, and nationally recognized standards like the Common Core State Standards and ISTE Standards for Students have pointedly emphasized the importance of “21st century skills” in K-12 education while simultaneously offering some clear guidance for what CT can look like in action. 

But what about higher education?  The implementation of CT in higher education classrooms is noticeably harder to call out, especially outside of computer science and engineering classrooms.  In my opinion, this is likely due to a number of factors including, but not limited to:

  1. Lack of collegial collaboration:  higher education disciplines are notoriously siloed. Meaningful integration of CT concepts outside of computer science and engineering programs demands intentional professional development for faculty, as well as interdisciplinary cooperation, both of which can be less accessible in higher education.
  2. Lack of resources: there is relatively little literature available which provides ideas for practical application of CT outside of computer science programs (i.e. coding and computer programming) at the postsecondary level. Additionally, published standards often lean more heavily towards K-12 education.
  3. Questions of applicability: the humanities often resist algorithmic ways of knowing because there is so much value placed on interpretation, subjectivity, and open debate about meaning (Czerkawski & Lyman, 2015).
  4. Just getting started: there is growing interest in translating CT pedagogy into a wide variety of disciplines in higher education (and K-12 for that matter), but the research and discussions are just getting started.  There is much yet to be explored.

Knowing that many STEM instructors in higher education automatically incorporate CT in their approach to teaching and learning because of the nature of their field, and knowing that engaging with CT in courses devoted to coding and programming are already integral to computer science and engineering majors, I seek to offer a few alternative examples of CT as it has been used to enhance teaching in learning in other kinds of higher education environments:

  • In a professional writing course taught at the undergraduate level, CT was used to systemize the writing process.  It called for a “deconstructive approach, breaking down the task of structured authoring into multiple layers of abstraction, and teaching each layer independently.” (Lyon & Magana, 2020, p. 1182)
  • In the fine arts, CT can be used as a tool to enhance creativity.  In one example, CT was used to create an organized system for tracing the origins of musical composers, which in turn inspired new creative endeavors based on the organized data. “…Algorithmic composition in music is, effectively, a human-computer collaboration–the computer serving as a tool that extends the composer’s ability to explore new musical ideas” (Edwards, 2011, p. 67)
  • The Stanford Literary Lab famously applied CT via Graph Theory to perform a “network analysis of character relationships and interactions” in a series of Shakespeare’s plays (Czerkawski & Lyman, 2015).
  • In the life sciences, CT has been used to inform systems theory and how to teach and understand biological processes, such as genetics, in an organized, logical fashion (Czerkawski & Lyman, 2015).
  • Utilizing a process dubbed “creative programming,” instructors may engage learners in the process of designing and developing an original work through coding. In this collaborative approach, learners are encouraged to co-construct knowledge in an interdisciplinary way. Examples might be to have students in a history course (co-)create a rendering of a city at a given historical period, or to present a traditional story in a visual programming tool like Scratch. In this kind of activity, learners must use skills and knowledge in mathematics, technology, language arts, and social sciences. (Romero et. al, 2017, para. 3)

Modeling and simulation activities are excellent examples of CT at work, and these types of learning activities can certainly extend themselves to many types of fields and disciplines.  Consider a learning activity where a group of undergraduate philosophy majors create a simulated narrative presentation wherein a human “character” makes a series of daily choices based on their moral philosophy or framework–almost like a “Choose Your Own Adventure” novel meets systems theory within one, or multiple, philosophical frameworks.  The simulation itself could be a computer-based product (or not), but regardless, the learning activity would draw upon many tenets of CT while also demonstrating in-depth knowledge of the discipline-specific subject matter.

All fields and disciplines require problem solving in some form.  Thus, it is reasonable to assume that CT may be useful in expanding the human ability to effectively problem solve in all fields.  In one study comparing the use of CT by an undergraduate computer science student and an art student, the researchers found that both students “…used various CT skills when solving all [italics added] problems, and the application of CT skills was influenced by their background, experiences, and goals.” (Febrian et. al., 2018, para. 1)  Regardless of training, background, or chosen major, CT enables postsecondary students to become more efficient problem solvers in all areas of life, teaching them to recognize computable problems and approach the problem-solving process as skillfully as possible (Czerkawski & Lyman, 2015).

References

Czerkawski, B.C. & Lyman, E.W. (2015). Exploring issues about computational thinking in higher education. TechTrends 59(2), 57–65. https://doi.org/10.1007/s11528-015-0840-3 

Edwards, M. (2011). Algorithmic composition: Computational thinking in music. Communications of the ACM, 54(7), 58-67. doi:10.1145/1965724.1965742  

Febrian, A., Lawanto, O., Peterson-Rucker, K., Melvin, A., & Guymon, S. E. (2018). Does everyone use computational thinking?: A case study of art and computer science majors. Proceedings of the ASEE Annual Conference & Exposition, 1–16.

Lyon, J. & Magana, A. (2020). Computational thinking in higher education: A review of the literature. Computer Applications in Engineering Education 28(5), 1174-1189. https://doi.org/10.1002/cae.22295

Romero, M., Lepage, A., & Lille, B. (2017). Computational thinking development through creative programming in higher education. International Journal of Educational Technology in Higher Education 14(42). https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-017-0080-z

Wing, J. (2006). Viewpoint: Computational thinking. Communications of the Association for Computing Machinery (49)3, 33-35. https://dl.acm.org/doi/fullHtml/10.1145/1118178.1118215?casa_token=DY3JiA-SOKMAAAAA:OYN4CIuf3LvuR1v4IiYsKQ-2J1KQMV6e0k6skWtib9uI02IKHhX9fEEA7rQC459Lk39QGworokaU 

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