Technology-mediated peer learning [electronic resource] : exploring an emerging trend in science education with a new framework for differentiating classroom interventions

President Obama recently launched the Educate to Innovate campaign with the intent to bolster the performance of US students in science, technology, engineering, and mathematics (STEM). This is in response to the US placing 21st out of 30 developed nations on the 2006 Program for International Student Assessment (PISA) comparison. Educate to Innovate is founded on the belief that if the US is going to be at the world's forefront of technology and innovation in the 21st century, its STEM education must improve relative to its international counterparts. Among the primary goals of Obama's program is the development of critical thinking skills and the expansion of STEM education to traditionally underrepresented groups in the sciences, which includes women. Clickers, which are wireless devices that encourage student participation through anonymous voting that can be tabulated and displayed in real time, have the potential to change the dynamics of science classrooms. Millions of college students have used clickers, prompting the National Resource Council (2000) to identify clickers as a promising new trend in education. In a review of 76 papers surrounding clicker use, MacArthur and Jones (2008) found that student collaboration has always been present in studies where statistically significant learning gains were detected. The pedagogy of Peer Instruction (Mazur, 1997) is a popular example of utilizing clickers to facilitate peer collaboration. During Peer Instruction (PI), students anonymously vote on multiple-choice, conceptually based questions with handheld clickers. PI incorporates clicker votes into a feedback loop where students are made privy to class-wide voting trends, asked to discuss their voting rationale with a peer, and then asked to re-vote on the same question with the overarching goal of reaching consensus. Evidence suggests this PI cycle is associated with statistically significant improvements in conceptual understanding over traditional lecture instruction (Crouch & Mazur, 2001; Fagen, Crouch, & Mazur, 2002). There is also evidence that classrooms utilizing the PI cycle can alleviate gender gaps that exist prior to instruction (Lorenzo, Crouch, & Mazur, 2006). Despite the successes of Peer Instruction at the postsecondary level, empirical assessments of clickers and PI in K-12 are almost nonexistent. In one of the few K-12 studies, Cummings and Roberts (2008) found strong and positive correlations between prior student ability and learning gains via exposure to PI -- higher achieving students seemed to thrive in PI environments while lower achieving students appeared to be left even further behind. If student preparation is a major factor in how much students benefit from pedagogy like PI, places like diverse urban high schools may require substantial modifications to PI if it is to help their students the way it is reported to help students at the postsecondary level. A deeper theoretical understanding behind the prior successes of PI can assist the adaption of PI to a younger and more diverse group of science learners. However, very little theoretical discussion is advanced for how Peer Instruction results have been achieved in prior studies. Developers of PI suggest that in between clicker votes on a conceptual question, students who know the correct answer essentially transmit their thinking to peers who originally answered incorrectly, thereby increasing the percentage of the class answering correctly upon re-vote (Crouch & Mazur, 2001; Mazur, 1997). In contrast, Smith et al. (2009) demonstrated that even when no member of a peer discussion group originally knows the right answer during PI, they are able to subsequently answer similar questions correctly at a rate that is statistically better than random guessing. Smith et al. interpret this finding to suggest "a more constructivist explanation ... students are arriving at conceptual understanding on their own, through the process of group discussion and debate" (p. 124). While constructivism posits that knowledge is subjectively created as opposed to objectively acquired, it does not provide an explicit framework by which to compare the relative effects of various learner-centered techniques. The constructive adjective -- in addition to adjectives such as active and interactive -- have been frequently attached to various activities in student-centered pedagogies like Peer Instruction, but much less frequently have these terms been explicitly defined and tested against each other (Chi, 2009). This study explores PI through a new theoretical framework that purports to make such comparisons amenable to empirical testing. Chi's (2009) passive-active-constructive-interactive (PACI) framework for learning activities overcomes the limitations of constructivism by permitting various learner-centered techniques to be both differentiated and adjudicated with empirical evidence. As Peer Instruction consists of multiple learning activities, the PACI framework provides both a classification scheme for each PI activity and testable hypotheses regarding the varying degrees of learning each PI activity can theoretically facilitate. Table 2.2 (Chapter 2) demonstrates how key stages of the PI cycle can be classified under the PACI framework and provides a theoretical basis for these classifications. As few empirical projects can carefully test more than a subset of the theories from which they are based, this study focused on precisely the component of the Peer Instruction cycle that Smith et al. (2009) believe facilitates improved conceptual understanding -- the use of time spent between clicker votes. More specifically, PACI was used to classify various activities between clicker votes and make predictions as to which of these activities best promote conceptual learning. Rationale for selection of activities between clicker votes was based on pilot testing, which will be explained in the Method and Procedure (Chapter 3). PACI hypothesizes that as instruction moves from passive → active → constructive → interactive, theoretically there should be deeper learning outcomes as you move along this progression (Chi, 2009; Fonseca & Chi, 2010). These hypotheses are supported empirically by Chi's review of multiple studies that are applicable to the PACI classification scheme. This dissertation supplements these empirical results with extensive theoretical grounding for each PACI hypothesis. The predictions of PACI were put to the test in this study of Peer Instruction, namely by measuring conceptual learning gains for students assigned to PI activities with differing PACI classifications. As depicted in Figure 2.1 (Chapter 2), students exhibit variation in academic performance and demographics, and these variations were interpreted as the student input to the PI cycle. After being exposed to the various activities of PI, conceptual learning gains are intended to be the output of the PI cycle. Between input and output are multiple iterative cycles of PI in a conceptual physics classroom. How students spend time between clicker votes is where Smith et al. (2009) called for a more constructivist explanation to the successes of PI, and hence the time between clicker votes is where the following two research questions are situated: Research Question #1. How do differing interventions between clicker votes associate with conceptual learning gains in secondary physics classrooms? Research Question #2. Do the associations explored in the first research question have interactions with gender and/or socioeconomic status? Three years of research has been conducted with two physics instructors implementing Peer Instruction at a suburban high school in the San Francisco Bay Area. The study site was chosen as the school is both diverse (66% Latino/a; 51% Title 1) and its teachers have launched an initiative to incorporate educational technology. Multiple summers were spent with teachers co-developing conceptual questions to be used in the study. Called Braincandy, these questions are written to be sensitive to literacy levels commensurate with a diverse high school. Pilot testing of PI utilizing Braincandy questions indicated that some student discussions would rapidly digress, and hence both teachers attempted to improve time on task by having some students write in a journal to supplement peer discussion. This writing intervention is classified as a constructive activity under the PACI framework, while student discussion is classified as interactive. The presence of two different modalities between clicker votes naturally suggested a more controlled experiment testing the PACI prediction that interactive activity (i.e., talking) should yield deeper learning than constructive activity (i.e., writing). Furthermore, some instructors believe offering a clear explanation for a question is more efficient than asking students to reach voting consensus on their own (Smith et al., 2009). Hence a supplemental lecture intervention is explored as well. As lecture is classified as passive under PACI, the framework hypothesizes that both the written and verbal activities should yield deeper learning than lecture between votes. These combinations of passive, constructive, and interactive interventions between clicker votes comprised the four experimental conditions of this dissertation study -- their methodological description and hypotheses based on PACI classification are summarized in Table 3.1 (Chapter 3). To test the PACI hypotheses, four class periods received a semester of conceptual physics instruction from the same instructor. Each of these four conceptual physics classrooms were taught at the same level of difficulty to students ranging from grades 9-12 in each period. The physical classroom, assignments, quizzes, textbook, lesson plans, and Braincandy questions for each cycle of Peer Instruction were ... .

Keywords: Education.
Advisor: Antonio Anthony Lising
Brown Bryan Anthony primary advisor. Thesis advisor
Osborne Jonathan advisor. Thesis advisor