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Timothy G. Harrison; Michael T. Davies-Coleman; Alison C. Rivett; M. Anwar H. Khan; Joyce D. Sewry; Magdalena Wajrak; Nicholas M. Barker; Jonny Furze; Sophie D. Franklin; Linda Sellou; Naomi K. R. Shallcross; Dudley E. Shallcross – Journal of Chemical Education, 2024
Climate change is of great concern to all age groups but in particular to children. "Simple" climate models have been in place for a long time and can be used effectively with post-16 students. For younger children, modifications are required, and we describe in this paper the development and use of two such models. The first (the Granny…
Descriptors: Foreign Countries, Climate, Models, Elementary Secondary Education
Zeynab Mohseni; Italo Masiello; Rafael M. Martins; Susanna Nordmark – Journal of Learning Analytics, 2024
Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this…
Descriptors: Learning Analytics, Visual Learning, Visualization, Intervention

Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing