HEEL‑seminarium
Nu har det blivit dags för årets sjätte HEEL-seminarium. Temat denna gång är hur innovativ design av utbildning kan stödja lärande.
Varmt välkomna till årets sjätte HEEL-seminarium. Temat den 16 december är hur innovativ design av utbildning kan stödja lärande. Under den första presentationen diskuterar Asuka Ohagi från Umeå universitet ett pågående arbete kring lärarkompetens och innovativ design av utbildning. Den andra presentationen är från the Open University of the Netherlands. Krist Shingjergjis studie berör system för att detektera studenters känslomässiga upplevelse av nätbaserad undervisning.
Dag och tid: 16 december, kl 10.00 - 12.00
Plats: Online via Zoom. Klicka här för att komma till mötet.
Information in english
Most welcome to the sixth HEEL seminar of 2024. Anyone interested in issues of digital technology, learning and higher education might benefit from participating. The theme for the HEEL seminar on the 16th of December is how innovative designs of education can support learning. The first presentation is from Asuka Ohagi, Umeå University. It discusses the relationship between teachers’ competence and innovative learning and teaching designs. The second presentation is from Krist Shingjergji, the Open University of the Netherlands. The study concerns how AI systems can detect learning-related emotional states in online classrooms.
Time and date: December 16th, 10.00 - 12.00.
Place: Online via Zoom. Click here to get the link.
Exploring teacher innovative learning environment competency in compulsory schools
Asuka Ohagi, Umeå University
More than 1,000 new schools are expected to be built in Sweden in the next 15 years including the schools with contemporary designs often referred as innovative learning environments (ILE) that are innovative, modern, and flexible enhancing the students’ 21st century skills. The aim of the team project is to contribute new knowledge about: (i) what kinds of practice play out in ILEs in terms of power and control, (ii) practice-takers (i.e. teachers) perceptions of educational change and how it challenges previous traditions for organising schools, and (iii) how a concept of student-centred learning evolves over time from the perspective of practice-takers. This will be achieved by targeting the collective learning process to understand how practice-takers learn, receive, and respond to the new school organisation and ILEs. Based on this team project, my thesis will be looking at the teacher competency on managing ILE schools and how it correlates with students’ outcomes. It will be a mixed method study starting with qualitative research. Based on the literature review, the teacher competency for ILEs is divided in 3 strands; Spatial, AI and Collaboration and this will be observed first qualitatively examining data from interviews, classroom observations and questionnaires. Students’ 21st century skills such as resilience and teamwork will be looked at as well. This is primarily to verify the literature; whether the three stands of competencies and students’ outcomes reflect the station in Swedish schools. As a next step, I plan to do a large-scale quantitative study on teachers and students in Swedish ILE schools. Questionnaires will be created to measure the teachers’ epistemological knowledge of ILE competencies and student’s 21st century skills. The study aims to show the effectiveness and advantages of ILE schools over traditional schools.
Sense the Classroom
Krist Shingjergji, The Open University of the Netherlands
As online classrooms continue to grow in popularity, the need for systems capable of detecting learning-related emotional states has become increasingly relevant. Artificial Intelligence often offers promising solutions. However, most existing studies focus on recognizing basic emotions, such as happiness or disgust, rather than learning-centered affective states (LCAS), like boredom or confusion, which are more relevant in educational contexts. In our study, we aim to address this gap by exploring the relationship between non-verbal cues and LCAS within the context of online classrooms. Using tailored, standardized stimuli, we seek to identify patterns that can inform and enhance AI systems designed to detect LCAS, including boredom, confusion, frustration, engagement, and curiosity, in online learning environments. In this presentation, we are going to present the background of the problem, discuss the current approach and the strategies for conducting the proposed study.
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