Graduate Thesis Or Dissertation

 

Technology to promote concept-based, active learning and enable education research Public Deposited

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  • This dissertation centers on development of two web-based, in class learning tools, the AIChE Concept Warehouse (CW) and the Web-based Interactive Science and Engineering Learning Tool (WISE), and describes the investigation of student learning through their use. The intent of these tools is to promote deeper conceptual understanding in students through engaging them in active learning pedagogies in the classroom. While the tools provide many useful features, this dissertation will focus primarily on a line of research into activities afforded by the technology’s ability to facilitate the presentation of concept questions to individual students in class and the subsequent collection of student responses in the form of multiple-choice answer selections and associated short written reflections justifying that answer choice. The dissertation presents four studies that investigate aspects of student learning using these tools in the active learning classroom. The first study investigates a structured pedagogy called peer instruction. In peer instruction students first answer a question individually, then form small groups where they discuss their answers and explain their reasoning, and finally re-answer the same question individually. The effect of displaying a histogram of responses to the class of their individual answer selections before group discussion is investigated. It found that students improve their understanding when engaging in peer instruction even if they answered correctly at first and that students tend to change to the popular answer irrespective of the histogram. It also found that even though the histogram does not appear to influence correct answer selections, it did influence self-reported confidence ratings. The second study uses a crossover experimental design to investigate the influence of prompting students to write an explanation justifying their answer choice when they respond individually. Results show improved thinking with written explanations. It argues that improved thinking is prompted by the students’ construction of logical arguments to justify their answer choices. The third and fourth studies further explore written explanations. The third illustrates the novel use of word clouds as a quick analysis method for large quantities of written explanations, and describes the integration of that feature into the CW. The fourth study characterizes the amount of time that it takes for students to answer questions. The results show that response time is affected by writing an explanation, whether students chose the correct multiple choice answer or not, and the question difficulty. Finally, some preliminary data are presented on developing a psychometric measure, based on modified Item Response Theory (IRT), to provide an automated mechanism of question quality control in the CW.
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