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1. Teacher Actions to Foster Creativity in Calculus

   Satyam, V.R. (January 2022, Proceedings of the 24rd Annual Conference on Research in Undergraduate Mathematics Education)

   S. Karunakaran, Z. Reed (Ed.)

   Fostering mathematical creativity in the classroom requires intentional actions on the part of the instructor. We examine the teaching actions that students in a creativity-based Calculus I course report as contributing to their sense of creativity. Based on interview data, we found the four overall types of teaching actions: Task-Related, Teaching-Centered, Inquiry Teaching, and Holistic Teaching. We discuss subtypes as well as concrete actions, to provide actionable steps practitioners can take to foster students’ creativity. 

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2. Exploring Practical Measures as an Approach for Measuring Elementary Students’ Attitudes Towards Computer science

   Shehzad, U; Clarke-Midura, J; Recker, M (April 2024, American Educational Research Association)

   This paper presents a novel approach for predicting the outcomes of elementary students’ participation in computer science (CS) instruction by using exit tickets, a type of practical measure, where students provide rapid feedback on their instructional experiences. Such feedback can help teachers to inform ongoing teaching and instructional practices. We fit a Structural Equation Model to examine whether students' perceptions of enjoyment, ease, and connections between mathematics and CS in an integrated lesson predicted their affective outcomes in self-efficacy, interest, and CS identity, collected in a pre- post- survey. We found that practical measures can validly measure student experiences. 

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3. Experience with Authentic Practice in an Engineering RET: Perceptions of Teachers, Mentors and Independent Observation

   Crippen, Kent J; Evans, Gayle N; Scherer, Christine G; Spillman, Courtney (January 2020, 2020 NARST International Conference)

   This study advances our design and development goal of creating a valid and reliable observation protocol for science and engineering practices (SEPs) experienced by participants working in research laboratories under the auspices of RET. This protocol offers the potential for addressing persistent questions related to participant experience by looking inside the blackbox of apprenticed professional research practice. Framed by cognitive apprenticeship and situated in an engineering RET for K-5 teachers (EEC-1711543), we independently document the SEPs which were consistently experienced across contexts and thus define a generalized teacher experience. Further, we identify key associations among the teacher's perception of their work, an independent observation and that reported by their graduate student mentors. Findings indicate that perception of involvement with any particular practice and not actual experience was a more important predictor of confidence. Perhaps most striking was the negative relationship between teacher confidence when working with mentors (r=-.242), which is similarly described by the mentors for working with teachers (r=-.356). This implies a strong need for further work and support for helping these individuals to understand each other’s goals and perspectives and for finding a way to work together that generates mutual feelings of confidence and satisfaction. 

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4. Sensor-Free Predictive Models of Affect in an Online Learning Environment

   Harrison, A (January 2018, Proceedings of the Eleventh International Conference on Educational Data Mining)

   A significant amount of research has illustrated the impact of student emotional and affective state on learning outcomes. Just as human teachers and tutors often adapt instruction to accommodate changes in student affect, the ability for computer-based systems to similarly become affect-aware, detecting and personalizing instruction in response to student affective state, could significantly improve student learning. Personalized and affective interventions in tutoring systems can be realized through affect-aware learning technologies to deter students from practicing poor learning behaviors in response to negative affective states and to optimize the amount of learning that occurs over time. In this paper, we build off previous work in affect detection within intelligent tutoring systems (ITS) by applying two methodologies to develop sensor-free models of student affect with only data recorded from middle-school students interacting with an ITS. We develop models of four affective states to evaluate and determine significant predictors of affect. Namely, we develop a model which discerns students’ reported interest significantly better than majority class. 

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5. PhDepression: Examining How Graduate Research and Teaching Affect Depression in Life Sciences PhD Students

   https://doi.org/10.1187/cbe.21-03-0077  

   Gin, Logan E.; Wiesenthal, Nicholas J.; Ferreira, Isabella; Cooper, Katelyn M. (September 2021, CBE—Life Sciences Education)

   Gardner, Grant Ean (Ed.)

   Graduate students are more than six times as likely to experience depression compared with the general population. However, few studies have examined how graduate school specifically affects depression. In this qualitative interview study of 50 life sciences PhD students from 28 institutions, we examined how research and teaching affect depression in PhD students and how depression in turn affects students’ experiences teaching and researching. Using inductive coding, we identified factors that either positively or negatively affected student depression. Graduate students more commonly mentioned factors related to research that negatively affected their depression and factors related to teaching that positively affected their depression. We identified four overarching aspects of graduate school that influenced student depression: the amount of structure in teaching and research, positive and negative reinforcement, success and failure, and social support and isolation. Graduate students reported that depression had an exclusively negative effect on their research, primarily hindering their motivation and self-confidence, but that it helped them to be more compassionate teachers. This work pinpoints specific aspects of graduate school that PhD programs can target to improve mental health among life sciences graduate students. 

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