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1. Student interaction discourse moves: characterizing and visualizing student discourse patterns

   https://doi.org/10.1186/s43031-022-00068-9  

   Nennig, Hannah T.; States, Nicole E.; Montgomery, Marika T.; Spurgeon, Sidney G.; Cole, Renée S. (January 2023, Disciplinary and Interdisciplinary Science Education Research)

   Abstract Student-centered instruction allows students to take ownership over their learning in the classroom. However, these settings do not always promote productive engagement. Using discourse analysis, student engagement can be analyzed based on how they are interacting with each other while completing in-class group activities. Previous analyses of student engagement in science settings have used methods that do not capture the intricacies of student group interactions such as the flow of conversation and nature of student utterances outside of argumentation or reasoning. However, these features are important to accurately assess student engagement. This study proposes a tiered analytical framework and visualization scheme for analyzing group discussion patterns that allow for a detailed analysis of student discourse moves while discussing scientific topics. This framework allows a researcher to see the flow of an entire conversation within a single schematic. The Student Interaction Discourse Moves framework can be used to extend studies using discourse analysis to determine how student groups work through problems. 

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2. Embedded student formative reporting to promote student metacognition and instructor pedagogical adjustments

   https://doi.org/10.55632/pwvas.v95i2.948  

   Richards-Babb, Michelle (April 2023, Proceedings of the West Virginia Academy of Science)

   Timely, formative feedback is important for instructors and students. In this project, “embedded students” provided instructors with formative feedback through anonymized reports. Students enrolled in preparatory chemistry course sections in fall 2022 self-selected to submit reports documenting their ongoing experiences in learning chemistry content. Embedded students journaled about (i) hours devoted to the course; (ii) topic-specific content mastery, comfort, and confusion; and (iii) instructor pedagogy. An average of 108 reports per week were anonymized and shared with instructors. Instructor effort was limited to agreeing to receive the weekly reports, look them over, and potentially use them to inform upcoming teaching. Embedded students benefited by thinking about their learning in the class (metacognition) and focusing their learning for the upcoming week. Overall, 300 distinct students submitted 1,513 weekly reports, with overall means of 2.81 hours per week of self-reported time devoted to attending lecture, 4.75 hours per week of self-reported time engaged in additional study, and 7.56 hours per week of self-reported total time devoted to the course. Instructors reported reading over 87% of the reports and using feedback to make an average of 4.6 instructional adjustments ranging from working additional practice problems on difficult concepts, providing answer keys to extra problems, implementing problem-solving/review days, and reviewing difficult material or content from earlier in the course. Instructors indicated that the weekly reports contributed to “instructor beneficence”. Students “felt heard” especially when instructors explicitly and constructively addressed comments from the weekly reports. This work is partially supported by the NSF-funded First2 Network. 

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3. Simulation Technology and Student Engagement

   Aji, C. A. (January 2020, The 2020 ASEE Gulf-Southwest Annual Conference)

   null (Ed.)

   An authentic learning environment with the integration of technology can effectively engage students and improve their academic performance. Technology can support learning situations that relate to real life, and provide opportunities for inquiry and collaboration, fostering engagement. This paper will provide details of an authentic learning environment that utilizes flight simulation software to engage middle school students in the learning of several math and science concepts. Active learning lessons were developed using missions flown on the flight simulator. The pedagogical approach was implemented in a one-week long summer camp for students from rural counties with low socio-economic status. Data on student attitudes towards STEM was collected using a 65-item questionnaire. The performance on the content taught during the camp was also measured. The pre-post data analysis indicated positive impact of the approach. The results of this study will be included in this paper. This work is supported by NSF Grant# 1614249. 

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4. Learning and Engineering Student Retention

   Ernst, J.V. (October 2019, Proceedings of the annual midyear conference of the Engineering Design Graphics Division American Society for Engineering Education)

   This study investigates institutional student retention for engineering majors in a 4-year university setting. Student participant retention was tracked for engineering majors within the institution following enrollment in an introductory to engineering design graphics course that employed active learning sequences. Student retention data was compared to an institution baseline of engineering majors following enrollment in the engineering design graphics course where differences were examined. Notable student retention differences were identified through analysis of the institutional baseline data for participating students. 

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5. Articulating the student mathematics in student contributions

   https://doi.org/10.51272/pmena.42.2020-354  

   Van Zoest, Laura R.; Stockero, Shari L.; Leatham, Keith R.; Peterson, Blake E.; Ruk, Joshua M. (December 2020, Mathematics Education Across Cultures: Proceedings of the 42nd Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education)

   Sacristán, A; Cortés-Zavala, J; null (Ed.)

   We draw on our experiences researching teachers’ use of student thinking to theoretically unpack the work of attending to student contributions in order to articulate the student mathematics (SM) of those contribution. We propose four articulation-related categories of student contributions that occur in mathematics classrooms and require different teacher actions:(a) Stand Alone, which requires no inference to determine the SM; (b) Inference-Needed, which requires inferring from the context to determine the SM; (c) Clarification-Needed, which requires student clarification to determine the SM; and (d) Non-Mathematical, which has no SM. Experience articulating the SM of student contributions has the potential to increase teachers’ 

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