EFFECTIVENESS OF HOLISTIC MENTAL MODEL CONFRONTATION IN DRIVING CONCEPTUAL CHANGE

Students' flawed conceptions can often be corrected during learning by successive contradictions from text sentences, allowing them to revise or replace their individual false beliefs as they read a text. Although this process supports learning new knowledge at a local level (i.e., individual propositions) it is less effective in facilitating systemic conceptual change. In contrast, constructive processes such as self-explaining can facilitate conceptual change through building a mental model from cumulative revisions of individual false beliefs. In the current experiment, I investigated whether comparing and contrasting examples can achieve the same outcome. Students (n=22) in the compare group were first shown a diagram of with their own flawed mental model, and then asked to compare it with a diagram of the correct model. This condition was compared with self-explaining the correct diagram (n=22), and a control condition in which students simply read the text twice (n=20). Results showed that the compare group performed better than the other two groups on questions requiring deep inference making

UNDERSTANDING THE INTERACTION BETWEEN STUDENTS’ THEORIES OF INTELLIGENCE AND LEARNING ACTIVITIES

Understanding the interaction between students’ motivation and instructional factors is critical for extending current cognitively based frameworks of learning, and can have important practical applications. Two laboratory experiments were conducted to explore how students’ implicit theories of intelligence interact with different types of learning activities. The ICAP framework by Chi (2009) organizes learning activities into passive, active, constructive, and interactive activities representing an increasing order of effectiveness. In Experiment 1, participants’ theories of intelligence were manipulated to be either entity or incremental, and the learning activity — inventing a formula to calculate variability, was manipulated to be constructive (inventing individually) or interactive (inventing collaboratively). It was predicted that individuals would learn procedurally simple aspects of the task better than collaborators regardless of their theory of intelligence, consistent with theories of collaboration and cognitive load. In contrast, while all collaborators were predicted to learn more conceptual knowledge than individuals, students with incremental theories were predicted to benefit more from collaboration than those with entity theories. Results showed that while individuals learned more than collaborators on procedural problems, the predicted interaction between collaboration and theories of intelligence on conceptual problems was not supported. Experiment 2 tested whether different types of constructive activities interacted with students’ theories of intelligence to affect learning outcomes. In this experiment, students’ theory of intelligence was manipulated to be either incremental or entity, and the type of constructive activity was manipulated to be either tell-and-practice instruction or invention. Two competing interaction hypotheses were proposed. Hypothesis one was that if invention activities led to more constructive processing, entity theorists would learn more from invention than from tell-and-practice instruction, but incremental theorists would learn equally well from either type of instruction. Hypothesis two was that if invention activities cause off-task behavior and impose excessive cognitive load, then tell-and-practice instruction would lead to better learning for entity theorists, however, both types of instruction would be equally effective for incremental theorists. Bayesian model selection provided some support for hypothesis one. Results of the two experiments are discussed in terms of their theoretical and practical significance

Introducing Low-Stakes Just-in-Time Assessments to a Flipped Software Engineering Course

Objective: We present a Teaching-as-Research project that implements a new intervention in a flipped software engineering course over two semesters. The short-term objective of the intervention was to improve students’ preparedness for live sessions. The long-term objective was to improve their knowledge retention evaluated in time-separated high-stakes assessments. Intervention: The intervention involved adding weekly low-stakes just-in-time assessments to course modules to motivate students to review assigned instructional materials in a timely manner. The assessments consisted of, per course module, two preparatory quizzes embedded within off-class instructional materials and a non-embedded in-class quiz. Method: Embedded assessments were deployed to two subgroups of students in an alternating manner. In-class assessments were deployed to all students. The impact of embedded assessments on in-class assessments and on final exam performance was measured. Results: Embedded assessments improved students’ preparedness for live sessions. The effect was statistically significant, but variable. Embedded assessments did not impact long-term knowledge retention assessed on final exam. We have decided to keep the intervention and deploy it to all students in the future

Analogical Scaffolding in Collaborative Learning

Past research has shown that collaboration can facilitate learning and problem solving (e.g., Azmitia, 1988; Barron, 2000). In the current work, we compared the effects of three collaborative learning conditions: prompts that encourage analogical comparison between examples, prompts that guide sequentially studying single examples, and traditional instruction (practicing problem solving), as students learned to solve physics problems in the domain of rotational kinematics. Preliminary results showed a significant problem type by condition interaction effect

Learning from Collaboratively Observing Videos during Problem Solving with Andes

Abstract. Learning by observation has long been a traditional method of learning. Recent work has pointed toward collaboratively observing tutoring as a promising new method for observational learning. Our current study tested this new method in the PSLC physics LearnLab where students were introduced to topic of rotational kinematics by observing videos while problem solving in Andes. The students were randomly assigned to a pairs condition that collaboratively observed a video of an expert tutoring or providing an example, or to a solo condition that observed a video of an expert worked example. Several robust and normal learning measures were collected, however, to date only multiple choice measures have been analyzed. Students ’ performance on the multiple choice questionnaires revealed significant pretest to posttest gains for all conditions. To date there no differences have been found among conditions. A trend in the data (p=.05) indicates a section effect that impacted the collaboratively observing of expert tutoring condition that still needs to be explored. However, if the non significant group differences stand, then one interpretation is that as long as students solved the problems correctly, it doesn’