Titlebook: Emerging Technologies for Education; 8th International Sy Zuzana Kubincová,Tianyong Hao,Jing Yang Conference proceedings 2024 The Editor(s)

ETHOS

書目名稱Emerging Technologies for Education影響因子(影響力)




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書目名稱Emerging Technologies for Education網(wǎng)絡(luò)公開度學科排名




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書目名稱Emerging Technologies for Education被引頻次學科排名




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書目名稱Emerging Technologies for Education讀者反饋




書目名稱Emerging Technologies for Education讀者反饋學科排名

obstruct

Social Innovation on Educational AI Developments. A Case Study on Social Participation on Designing . Generative AI tools require new models of technology development due to the complexity of their structure, from the creation of large datasets to the adjustment of biases to ensuring fairness of their results. The use of community-based research approaches to involve diverse groups and citizen sen

STALL

Empowering Collaboration Through Immersive Technologies: Fostering Intercultural Competenciesstudy explores and evaluates university students’ perceptions of their intercultural competencies and acceptance of emerging technology tools, specifically Metaverse, for virtual collaboration with people from other cultures. This research employs qualitative research methodology, specifically a cas

違抗

Fibrin

On the?Dynamic Generation of?Items Within an?Assessment Test Using Genetic Algorithmsthe most important parameters of this process, due to its impact on the development of the assessment implementation phase. This paper presents a development of a model of an assessment test generation using genetic algorithms with an additional type of item which is dynamically generated. The item

不可磨滅

不可磨滅

pulmonary-edema

Examining the Technological Pedagogical Content Knowledge (TPACK) of Biology Educators: A Case Studyervice educators in STEM-related disciplines, especially biology. By using the STEM-TPACK framework, the first phase of this research project adopted a quantitative approach and found the differences in readiness of in-service and pre-service biology teachers to implement STEM education as reflected

Communal

Online Performance Prediction Combined Prior Knowledge and Deep Learning Modelslyzing online learning behavior data can further improve teaching and assessment methods, enhance learning outcomes, and promote independent learning. However, it is a challenge for teachers to evaluate learning status and academic performance of each student through online learning systems. This st

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