Microgenetic learning analysis: A methodology for studying knowledge in transition

This paper introduces and exemplifies a qualitative method for studying learning, microgenetic learning analysis (MLA), which is aimed jointly at developing theory and at establishing useful empirical results. Among modern methodologies, the focus on theory is somewhat distinctive. We use two strategies to describe MLA. First, we develop a framework for comparing the focus and means of different methods, particularly qualitative methods, aimed at studying learning. Using the framework, we compare and contrast MLA with two better-known methods, microgenetic analysis and grounded theory. Second, we aim to schematize elements of MLA-from large-scale patterns of work to detailed analytical strategies-and to exemplify some of them in a case study using data collected some years prior to this elaboration of MLA

Microgenetic learning analysis: A methodology for studying knowledge in transition

This paper introduces and exemplifies a qualitative method for studying learning, microgenetic learning analysis (MLA), which is aimed jointly at developing theory and at establishing useful empirical results. Among modern methodologies, the focus on theory is somewhat distinctive. We use two strategies to describe MLA. First, we develop a framework for comparing the focus and means of different methods, particularly qualitative methods, aimed at studying learning. Using the framework, we compare and contrast MLA with two better-known methods, microgenetic analysis and grounded theory. Second, we aim to schematize elements of MLA-from large-scale patterns of work to detailed analytical strategies-and to exemplify some of them in a case study using data collected some years prior to this elaboration of MLA

Why complexity is important for learning

Symposium Chair: Olivia Levrini, University of Bologna Participants: Music, Math, and Time: Paradoxes and Affinities. Jeanne Bamberger, Massachusetts Institute of Technology Managing Perceptual and Conceptual Complexity Through the Use of Computational Representations. Orit Parnafes, University of California-Berkeley Embracing Complexity: A Necessary Path to Learning Modern Physics. Olivia Levrini, University of Bologna Managing the Profile of Complexity in Learning Physics. Andrea A. diSessa, University of California-Berkeley Discussant: David Hammer, University of Maryland Abstract. A shared assumption in physics education is that learning physics is complex. But two extremes are easy to recognize as ways of looking at and facing the complexity of physics learning. On one hand, complexity is considered a huge demotivational factor that, consequently, must be reduced as much as possible. On the other hand, complexity is considered as a feature of thinking and is not to be removed but rather organized in order to make it manageable by cognitive, emotional, rational tools. The four contributions of the symposium share the general assumption that complexity is important for learning. Each will provide interpretations of what is meant by complexity and what learning tools students should have for managing multi-faceted situations. Chair: Olivia Levrini, University of Bologna Participants: Music, Math, and Time: Paradoxes and Affinities. Jeanne Bamberger, Massachusetts Institute of Technology Managing Perceptual and Conceptual Complexity Through the Use of Computational Representations. Orit Parnafes, University of California-Berkeley Embracing Complexity: A Necessary Path to Learning Modern Physics. Olivia Levrini, University of Bologna Managing the Profile of Complexity in Learning Physics. Andrea A. diSessa, University of California-Berkeley Discussant: David Hammer, University of Marylan

Comparing expert and novice concept map construction through a talk-aloud protocol

Concept maps can be used as generative assessment tools to identify changes in learner’s understanding. However, concept map analysis usually only focuses on the final product. This case study used a talk aloud protocol to study and compare the concept map construction processes of novices and experts. Three biology experts (two researchers and one teacher) and three novices (9th and 10th grade high school students) constructed a concept map from a given list of concepts. Screen recording software was used to capture and contrast different stages of the concept map construction process, aligned with audio recordings of talk-aloud utterances. Findings suggest that final concept maps of high performing students cannot be distinguished from expert-generated maps. However, analysis of oral elaborations during the construction process revealed that experts often used the same link labels as novices but associated more complex knowledge with the label. Additionally, some final propositions would be considered incorrect without an additional oral explanation. Analysis of intermediate stages revealed insightful clusters and temporal flows that were no longer identifiable in the final map. Findings suggest extending concept map evaluation by complementing the final product with an analysis of intermediate stages and accompanying elaborations. Additionally, this study highlights that each expert created a different map and that therefore there is no single expert map. This observation is important when considering using a single expert-generated concept map as the reference to evaluate student-generated maps. Findings from study improve our understanding of concept map generation processes and our understanding of knowledge represented in concept maps

Translating between representations in a social context: a study of undergraduate science students' representational fluency

Interacting with and translating across multiple representations is an essential characteristic of expertise and representational fluency. In this study, we explored the effect of interacting with and translating between representations in a computer simulation or in a paper-based assignment on scientific accuracy of undergraduate science students' explanations regarding the underlying mechanisms of action potential. The study proposed that a simulation designed with scaffolded inquiry and with multiple dynamically linked representations fosters students to use greater scientific accuracy in speaking about a complex scientific phenomenon as well as to work with this complex knowledge in higher cognitive domains. Student explanations were analysed for use of accurate scientific language as they worked with the instructional tool as well as under test conditions. We also investigated the cognitive domain that students worked within as they created explanations of the phenomenon under study. The proportion of elaborations that occurred in higher-level cognitive domains such as applying, analysing, evaluating and synthesising was used to denote representational fluency. The rationale for this approach is discussed. Findings suggest that the simulation prompted students towards operating in higher cognitive domains in order to construct new knowledge and therefore promoted representational fluency. It also suggests that translating between representations in a simulation in a collaborative social setting contributes towards students' use of accurate scientific language. Students' perceptions expressed during the interviews confirmed the findings