Nathaniel Lasry

Peer instruction: From Harvard to the two-year college

We compare the effectiveness of a first implementation of peer instruction (PI) in a two-year college with the first PI implementation at a top-tier four-year research institution. We show how effective PI is for students with less background knowledge and what the impact of PI methodology is on student attrition in the course. Results concerning the effectiveness of PI in the college setting replicate earlier findings: PI-taught students demonstrate better conceptual learning and similar problem-solving abilities than traditionally taught students. However, not previously reported are the following two findings: First, although students with more background knowledge benefit most from either type of instruction, PI students with less background knowledge gain as much as students with more background knowledge in traditional instruction. Second, PI methodology is found to decrease student attrition in introductory physics courses at both four-year and two-year institutions.

The puzzling reliability of the Force Concept Inventory

The Force Concept Inventory (FCI) has influenced the development of many research-based pedagogies. However, no data exists on the FCI’s internal consistency or test-retest reliability. The FCI was administered twice to one hundred students during the first week of classes in an electricity and magnetism course with no review of mechanics between test administrations. High Kuder–Richardson reliability coefficient values, which estimate the average correlation of scores obtained on all possible halves of the test, suggest strong internal consistency. However, 31% of the responses changed from test to retest, suggesting weak reliability for individual questions. A chi-square analysis shows that change in responses was neither consistent nor completely random. The puzzling conclusion is that although individual FCI responses are not reliable, the FCI total score is highly reliable.

Just in Time to Flip Your Classroom

With advocates like Sal Khan and Bill Gates,1 flipped classrooms are attracting an increasing amount of media and research attention.2 We had heard Khans TED talk and were aware of the concept of inverted pedagogies in general. Yet it really hit home when we accidentally flipped our classroom. Our objective was to better prepare our students for class. We set out to effectively move some of our course content outside of class and decided to tweak the Just-in-Time Teaching approach (JiTT).3 To our surprise, this tweak—which we like to call the flip-JiTT—ended up completely flipping our classroom. What follows is narrative of our experience and a procedure that any teacher can use to extend JiTT to a flipped classroom.

The effect of multiple internal representations on context-rich instruction

We discuss n-coding, a theoretical model of multiple internal mental representations. The n-coding construct is developed from a review of cognitive and imaging data that demonstrates the independence of information processed along different modalities such as verbal, visual, kinesthetic, logico-mathematic, and social modalities. A study testing the effectiveness of the n-coding construct in classrooms is presented. Four sections differing in the level of n-coding opportunities were compared. Besides a traditional-instruction section used as a control group, each of the remaining three sections were given context-rich problems, which differed by the level of n-coding opportunities designed into their laboratory environment. To measure the effectiveness of the construct, problem-solving skills were assessed as conceptual learning using the force concept inventory. We also developed several new measures that take students’ confidence in concepts into account. Our results show that the n-coding construct is ...

When Talking Is Better Than Staying Quiet

The effectiveness of Peer Instruction is often associated to the importance of in‐class discussions between peers. Typically, a greater number of students have correct answers after peer discussions. However, other cognitive and metacognitive processes such as reflection or time‐on‐task may also explain this increase because students answering conceptual questions reflect more and spend more time thinking about their understanding. An identical sequence of conceptual questions was given to three groups of students. All groups were polled twice on each question. Between polls, students were asked either to discuss their choice with a peer, or to reflect for a minute (no discussion), or were given a distraction task (sequence of cartoons: no discussion and no reflection). Increases in the rates of correct answers between the first and the second poll were found across all conditions. The ‘Distract’ condition had a small but positive increase (3.4%). The ‘Reflect’ condition had a greater increase (9.7%) while the ‘Discuss’ condition had the greatest (21.0%). All conditions showed gains, possibly because of ‘testing effects’, though peer‐discussions clearly yield greatest increases. Our findings show that learning gains through peer discussions cannot be explained only by additional time‐on‐task or self‐reflection.

Are Most People Too Dumb for Physics

In last months issue of TPT, Michael Sobel turns our attention to the increasing number and broader population of students taking physics courses and urges us to reconsider how to better cater to their needs. We applaud the author for focusing our attention on this important issue. However, we find his proposal for teaching physics to nonscience majors problematic.

Are All Wrong FCI Answers Equivalent

The Force Concept Inventory (FCI) has been efficiently used to assess conceptual learning in mechanics. Each FCI question has one Newtonian answer and four wrong answers (distracters). Researchers and practitioners most frequently use measures of total score to assess learning. Yet, are all wrong answers equivalent? We conducted Latent Markov Chain Modeling (LMCM) analyses of all choices (right and wrong) on a subset of four FCI questions. LMCM assesses whether there are groups of students sharing similar patterns of responses. We infer that students sharing similar patterns also share similar reasoning. Our results show seven reasoning‐groups. LMCM also computes probabilities of transition from one reasoning‐group to another after instruction. Examining transitions between groups, we note a clear hierarchy. Groups at the top of the hierarchy are comprised of students that use Newtonian thinking more consistently but also choose certain wrong answers more frequently; suggesting that not all wrong answers ...

Effective variations of peer instruction: The effects of peer discussions, committing to an answer, and reaching a consensus

Peer Instruction (PI) is a widely used student-centered pedagogy, but one that is used differently by different instructors. While all PI instructors survey their students with conceptual questions, some do not allow students to discuss with peers. We studied the effect of peer discussion by polling three groups of students (N = 86) twice on the same set of nine conceptual questions. The three groups differed in the tasks assigned between the first and second poll: the first group discussed, the second reflected in silence, and the third was distracted so they could neither reflect nor discuss. Comparing score changes between the first and second poll, we find minimal increases in the distraction condition (3%), sizable increases in the reflection condition (10%), and significantly larger increases in the peer discussion condition (21%). We also examined the effect of committing to an answer before peer discussion and reaching a consensus afterward. We compared a lecture-based control section to three var...

What Should We Expect Students to Learn

A rejoinder to Sobels comment on “Are most people too dumb for physics?” We read Michael Sobels response with much interest and appreciate his enthusiasm and commitment to physics education. Yet, we continue to find that our goals and methods differ markedly. Foremost, because we do not agree that physics is a “different category” of hard which is accessible to a select few (i.e., “a certain sort of very bright student”), we cannot agree that ordinary, nonscience students must be taught a different kind of physics. We object to the idea of two “types” of physics—one for the layperson and one for the specialist. Physics must have relevance for everyone.

Losing it: The Influence of Losses on Individuals’ Normalized Gains

Researchers and practitioners routinely use the normalized gain (Hake, 1998) to evaluate the effectiveness of instruction. Normalized gain (g) has been useful in distinguishing active engagement from traditional instruction. Recently, concerns were raised about normalized gain because it implicitly neglects retention (or, equivalently, “losses”). That is to say, g assumes no right answers become wrong after instruction. We analyze individual standardized gain (G) and loss (L) in data collected at Harvard University during the first five years that Peer Instruction was developed. We find that losses are non‐zero, and that losses are larger among students with lower pre‐test performances. These preliminary results warrant further research, particularly with different student populations, to establish whether the failure to address loss changes the conclusions drawn from g.