Extended data for Play Smart: Utilizing Smart Environment for Understanding Group Play Activities to Foster Early Skill Development

Play Smart: Utilizing Smart Environment for Understanding Group Play Activities to Foster Early Skill Development

Institution

Eötvös Loránd University

Organizational Unit

PPK Institute of Psychology

Related programme

Psychology

Code

PSZM21-MO-ATIP-106

ECTS

4

ISCED code

0313 Psychology

Language of instruction

English

Academic term

1/2

Title

Play Smart: Utilizing Smart Environment for Understanding Group Play Activities to Foster Early Skill Development  hu

Play Smart: Utilizing Smart Environment for Understanding Group Play Activities to Foster Early Skill Development  en

Reading list Compulsory and recommended reading list Mandatory and recommended readings for the course will be specified and provided electronically in each semester. See readings on the topic below as examples: Fisher K et al. (2010) Playing around in school: Implications for learning and educational policy DOI: 10.1093/oxfordhb/9780195393002.013.0025 Celia A. Brownell (2011) Early developments in joint action. https://link.springer.com/article/10.1007/s13164-011-0056-1 Hanish L. D., Martin C. L., Fabes R. A., Leonard S., Herzog M. (2005). Exposure to externalizing peers in early childhood: homophily and peer contagion processes. Journal of abnormal child psychology, 33(3), 267–281. https://doi.org/10.1007/s10802-005-3564-6 Heravi B.M., Gibson J.L., Hailes S., Skuse D. (2018). Playground social interaction analysis using bespoke wearable sensors for tracking and motion capture Proceedings of the 5th International Conference on Movement and Computing, 1-8. https://www.researchgate.net/publication/326137665_Playground_Social_Interaction_Analysis_using_Bespoke_Wearable_Sensors_for_Tracking_and_Motion_Capture Komatsubara T., Shiomi M., Kaczmarek T. et al. (2019) Estimating Children’s Social Status Through Their Interaction Activities in Classrooms with a Social Robot. Int J of Soc Robotics 11, 35–48. https://doi.org/10.1007/s12369-018-0474-7

Reading list Compulsory and recommended reading list Mandatory and recommended readings for the course will be specified and provided electronically in each semester. See readings on the topic below as examples: Fisher K et al. (2010) Playing around in school: Implications for learning and educational policy DOI: 10.1093/oxfordhb/9780195393002.013.0025 Celia A. Brownell (2011) Early developments in joint action. https://link.springer.com/article/10.1007/s13164-011-0056-1 Hanish L. D., Martin C. L., Fabes R. A., Leonard S., Herzog M. (2005). Exposure to externalizing peers in early childhood: homophily and peer contagion processes. Journal of abnormal child psychology, 33(3), 267–281. https://doi.org/10.1007/s10802-005-3564-6 Heravi B.M., Gibson J.L., Hailes S., Skuse D. (2018). Playground social interaction analysis using bespoke wearable sensors for tracking and motion capture Proceedings of the 5th International Conference on Movement and Computing, 1-8. https://www.researchgate.net/publication/326137665_Playground_Social_Interaction_Analysis_using_Bespoke_Wearable_Sensors_for_Tracking_and_Motion_Capture Komatsubara T., Shiomi M., Kaczmarek T. et al. (2019) Estimating Children’s Social Status Through Their Interaction Activities in Classrooms with a Social Robot. Int J of Soc Robotics 11, 35–48. https://doi.org/10.1007/s12369-018-0474-7

Content of the course The course starts with introducing relevant literature and providing theoretical background to the practical work ahead. Next, introduction and practical skills in using the smart environment for skill assessment and training through play activities will be initiated in the Adaptation Research Group’s lab. Based on the acquired theoretical background, students are encouraged to try out play activities and develop their own ideas for skill training. Discussion about students’ ideas and related results from prior research will be initiated, preparing for the main quest: focusing on a specific research or methodological question to be answered on the field with child groups in kindergartens or schools. Multidimensional data collected in real time will be analyzed using Data Science methods. We will accomplish analyses together; students are expected to understand outcomes of these analyses and formulate adequate conclusions. Topic of the course Introduction to the topics of group play activities, skill development and novel digital solutions for analyzing play behavior Practical sessions on using devices of the smart environment (lab work and experimentation) Choosing a group assignment to utilize acquired theoretical and practical knowledge and formulate a specific research question and/or skill training quest Field studies: participating in ongoing research activities of the Adaptation Research Group Introduction to the analyses of multidimensional wearable sensor data – questions and answers Completion and presentation of the group assignment: summarizing the question raised and related findings and experiences. In-class discussion of each assignment. Feedback and evaluation of the course, future directions Learning activities, learning methods Lectures, practical classes, lab work and own experience, participation in field studies, group assignments, presentation.

Content of the course The course starts with introducing relevant literature and providing theoretical background to the practical work ahead. Next, introduction and practical skills in using the smart environment for skill assessment and training through play activities will be initiated in the Adaptation Research Group’s lab. Based on the acquired theoretical background, students are encouraged to try out play activities and develop their own ideas for skill training. Discussion about students’ ideas and related results from prior research will be initiated, preparing for the main quest: focusing on a specific research or methodological question to be answered on the field with child groups in kindergartens or schools. Multidimensional data collected in real time will be analyzed using Data Science methods. We will accomplish analyses together; students are expected to understand outcomes of these analyses and formulate adequate conclusions. Topic of the course Introduction to the topics of group play activities, skill development and novel digital solutions for analyzing play behavior Practical sessions on using devices of the smart environment (lab work and experimentation) Choosing a group assignment to utilize acquired theoretical and practical knowledge and formulate a specific research question and/or skill training quest Field studies: participating in ongoing research activities of the Adaptation Research Group Introduction to the analyses of multidimensional wearable sensor data – questions and answers Completion and presentation of the group assignment: summarizing the question raised and related findings and experiences. In-class discussion of each assignment. Feedback and evaluation of the course, future directions Learning activities, learning methods Lectures, practical classes, lab work and own experience, participation in field studies, group assignments, presentation.

Evaluation of outcomes Learning requirements, mode of evaluation and criteria of evaluation: The final grade will be based on quality and fluency of accomplishment of the group assignment activity on the classes.

Evaluation of outcomes Learning requirements, mode of evaluation and criteria of evaluation: The final grade will be based on quality and fluency of accomplishment of the group assignment activity on the classes.