Assessment

Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621

Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621

Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621

Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621

This study applied the many-facet Rasch measurement (MFRM) to assess students’ knowledge-in-use in middle school physical science. 240 students completed three knowledge-in-use classroom assessment tasks on an online platform. We developed transformable scoring rubrics to score students’ responses, including a task-generic polytomous rubric (applicable to the three tasks), a task-specific polytomous rubric (for each task), and a task-specific dichotomous rubric (for each task). Three qualified raters scored 240 students’ responses to the three tasks.

The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.

The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.

Contemporary views on what students should learn increasingly emphasize that students need to acquire more than a base of knowledge; they need to acquire the skills and abilities to use such knowledge in dynamic and flexible ways. To be most effective, learning environments need assessments that are aligned to these perspectives. Using a principled design framework can help guide assessment development toward such targets. Even when using a framework, however, thorny design challenges may arise.

Contemporary views on what students should learn increasingly emphasize that students need to acquire more than a base of knowledge; they need to acquire the skills and abilities to use such knowledge in dynamic and flexible ways. To be most effective, learning environments need assessments that are aligned to these perspectives. Using a principled design framework can help guide assessment development toward such targets. Even when using a framework, however, thorny design challenges may arise.

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four 2019 NAEP science assessment tasks were coded by content experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality.