Search results for " problem-solving skills"
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教員 21 世紀型スキルに資するグローバル教員研修に関する実践的研究 ― Edu21st 尺度による自己効力感の変容に着目してー [Teachers’ self-efficacy on 21st century skills : A case study of an in-service teac…
2022
本研究の目的は，大学教員養成におけるグローバル教員研修が，大学院生（現 職教員・大学生）の「教員 21 世紀型スキル」に関する自己効力感にどのような変容を もたらすかを明らかにすることである。研修は，１ . 対話型ボトムアップ研修，２ ．フィン ランドの教育改革研修，及び，３ ．教科連携の CLIL・STEAM に拠る授業訪問を特徴 とする。次世代の児童・生徒が，学びを実社会へ転移するような教育を実現する教員の 21 世紀型スキルとは何か，国際間比較をとおした俯瞰的な研修を目指す。研究方法は， 『Edu 21st：教員 21 世紀型スキルの自己効力感尺度』の 47 質問項目をもちいた事前 と事後の変容，およびポートフォリオ記述分析である。その結果，Edu21st（３ 因子構 造）で差が認められ，「分析的デザイン思考能力」で最も変化が大きいことが明らかにな り，異分野連携の協働中に起こる異質な考えに対する葛藤への価値付けが見られた。 peerReviewed
DISTANCE LEARNING AND COVID-19 FROM STUDENTS’ PERSPECTIVE: DO THEY HAVE THE SKILLS TO DEAL WITH THE UNPRECEDENTED SITUATION?
2021
As a result of the COVID-19 pandemic, more than 1,6 billion children worldwide were forced to discontinue face-to-face education and continue with distance learning (OECD, 2020). To many students as well as teachers this was their first experience with distance learning. Students' ability to adapt to distance learning varies and depends on different factors, including individual factors such as the ability to cope with new situations, solve problems and manage their own learning process. In order to successfully deal with the new circumstances in education, it is necessary to work at all levels - including the level of policy development, level of schools as organizations, and at the indivi…
Identifying childhood movement profiles and comparing differences in mathematical skills between clusters : A latent profile analysis
2021
The aims of this study were; 1) to identify different movement profiles in sixth graders, and 2) to investigate if there are differences in their mathematical basic (BasicMath) and problem solving (ProbSol) skills between existing movement profiles. The sample included 461 (223 girls, 238 boys) students with a mean age of 11.27 +/- .32 years from southern and middle Finland. A latent profile analysis (LPA) revealed four movement profiles: "poor movers", "average movers", "skilled movers" and "expert movers". These profiles differed substantially in their motor competence (MC) and health-related fitness (HRF). A multivariate analysis of variance (MANOVA) also revealed that "poor movers" and …