Join us to discuss peer instruction on Monday 7th December at 2pm GMT

Peer instruction is a tried and tested technique for teaching popularised by the Harvard physicist Eric Mazur. Join us to discuss the use of peer instruction in introductory computing via a paper by Leo Porter and his collaborators, [1] which won an award from the ACM SIGCSE Technical Symposium Top Ten Papers of All Time. Here is the abstract:

Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants in the classroom. Over the past five years, there have been a number of research articles regarding the value of PI in computer science. The present work adds to this body of knowledge by examining outcomes from seven introductory programming instructors: three novices to PI and four with a range of PI experience. Through common measurements of student perceptions, we provide evidence that introductory computing instructors can successfully implement PI in their classrooms. We find encouraging minimum (74%) and average (92%) levels of success as measured through student valuation of PI for their learning. This work also documents and hypothesizes reasons for comparatively poor survey results in one course, highlighting the importance of the choice of grading policy (participation vs. correctness) for new PI adopters.

As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details and meeting URLs.

References

  1.  Porter, Leo; Bouvier, Dennis; Cutts, Quintin; Grissom, Scott; Lee, Cynthia; McCartney, Robert; Zingaro, Daniel; Simon, Beth (2016). “A Multi-institutional Study of Peer Instruction in Introductory Computing”: SIGCSE ’16: Proceedings of the 47th ACM Technical Symposium on Computing Science Education 358–363. DOI:10.1145/2839509.2844642.

Join us to discuss why minimal guidance doesn’t work on Monday 2nd November at 2pm GMT

Minimal guidance is a popular approach to teaching and learning. This technique advocates teachers taking a back seat to facilitate learning by letting their students get on with it. Minimal guidance comes in many guises including constructivism, discovery learning, problem-based learning, experiential learning, active learning, inquiry-based learning and even lazy teaching. According to its critics, unguided and minimally guided approaches don’t work. Join us to discuss why via a paper [1] published by Paul Kirschner, John Sweller and Richard Clark, here is the abstract:

Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

This is a controversial, heavily cited and politically motivated paper which has provoked numerous rebuttals, making it an ideal candidate for a juicy journal club discussion! Thanks to Quintin Cutts for this months #paper-suggestions via our slack channel at uk-acm-sigsce.slack.com.

As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details and meeting URLs.

References

  1. Kirschner, Paul A.; Sweller, John; Clark, Richard E. (2006). “Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching”. Educational Psychologist. 41 (2): 75–86. DOI: 10.1207/s15326985ep4102_1 (see also altmetric.com/details/564640 for online attention scores)