The purpose of this study was to investigate a new methodology for detection of differences in middle grades students' math anxiety. A mixture partial credit model analysis was used to detect distinct latent classes based on homogeneities in response patterns. The analysis detected two latent classes. Students in Class 1 had less anxiety about apprehension of math lessons and use of mathematics in daily life, and more self-efficacy for mathematics than students in Class 2. Students in both classes were similar in terms of test and evaluation anxiety. Moreover, students in Class 1 were found to be more successful in mathematics, mostly like mathematics and mathematics teachers, and have better educated mothers than students in Class 2. Manifest variables of gender, attending private or public schools, and education levels of fathers did not differ among the latent classes. Characterizing differences between members of each latent class extends recent advances in measuring math anxiety.
Despite the critical role of teachers in the educational process, few advanced learning technologies have been developed to support teacher-instruction or professional development. This lack of support is particularly acute for middle school math teachers, where only 37% felt well prepared to scaffold instruction to address the needs of diverse students in a national sample. To address this gap, the Advancing Middle School Teachers’ Understanding of Proportional Reasoning project is researching techniques to apply pedagogical virtual agents and dialog-based tutoring to enhance teachers' content knowledge and pedagogical content knowledge. This paper describes the design of a conversational, agent-based intelligent tutoring system to support teachers' professional development. Pedagogical strategies are presented that leverage a virtual human facilitator to tutor pedagogical content knowledge (how to teach proportions to students), as opposed to content knowledge (understanding proportions). The roles for different virtual facilitator capabilities are presented, including embedding actions into virtual agent dialog, open-response versus choice-based tutoring, ungraded pop-up sub-activities (e.g. whiteboard, calculator, note-taking). Usability feedback for a small cohort of instructors pursuing graduate studies was collected. In this feedback, teachers rated the system ease of use and perceived usefulness moderately well, but also reported confusion about what to expect from the system in terms of flow between lessons and support by the facilitator.
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