Emotional climate of a pre-service science teacher education class in Bhutan

This study explored pre-service secondary science teachers’ perceptions of classroom emotional climate in the context of the Bhutanese macro-social policy of Gross National Happiness. Drawing upon sociological perspectives of human emotions and using Interaction Ritual Theory this study investigated how pre-service science teachers may be supported in their professional development. It was a multi-method study involving video and audio recordings of teaching episodes supported by interviews and the researcher’s diary. Students also registered their perceptions of the emotional climate of their classroom at 3-minute intervals using audience response technology. In this way, emotional events were identified for video analysis. The findings of this study highlighted that the activities pre-service teachers engaged in matter to them. Positive emotional climate was identified in activities involving students’ presentations using video clips and models, coteaching, and interactive whole class discussions. Decreases in emotional climate were identified during formal lectures and when unprepared presenters led presentations. Emotions such as frustration and disappointment characterized classes with negative emotional climate. The enabling conditions to sustain a positive emotional climate are identified. Implications for sustaining macro-social policy about Gross National Happiness are considered in light of the climate that develops in science teacher education classes.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

Context-based assessment: Creating opportunities for resonance between classroom fields and societal fields

There is on-going international interest in the relationships between assessment instruments, students’ understanding of science concepts and context-based curriculum approaches. This study extends earlier research showing that students can develop connections between contexts and concepts – called fluid transitions – when studying context-based courses. We provide an in-depth investigation of one student’s experiences with multiple contextual assessment instruments that were associated with a context-based course. We analyzed the student’s responses to context-based assessment instruments to determine the extent to which contextual tests, reports of field investigations, and extended experimental investigations afforded her opportunities to make connections between contexts and concepts. A system of categorizing student responses was developed that can inform other educators when analyzing student responses to contextual assessment. We also refine the theoretical construct of fluid transitions that informed the study initially. Implications for curriculum and assessment design are provided in light of the findings.