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Investigating the Perceptions of AI-Powered Applications in Science Education: A TAM-Based Study

Year: 2025

Type: article

Abstract: The rapid integration of Artificial Intelligence (AI) in education offers transformative opportunitiesto enhance teaching and learning practices in science education. This study investigates theusability and acceptance of two newly developed AI-powered applications, a platform forstreamlining teachers’ instructional practices and a conversational assistant for supportingstudents’ self-study routines, using the Technology Acceptance Model (TAM) as a guidingframework. Hands-on workshops were conducted across four European countries, engaging 117participants (32 teachers and 85 students) who evaluated the applications through TAM-basedquestionnaires assessing Perceived Ease of Use (PEOU), Perceived Usefulness (PU), AttitudesToward Use (ATU), and Self-Efficacy (SE). The findings reveal that both groups rated theapplications positively across all TAM factors, indicating broad acceptance. However, PU receivedthe lowest scores, highlighting the need to better align the applications with specific educationalneeds. Teachers demonstrated significantly higher ATU and SE scores than students, reflectinggreater enthusiasm and confidence, underlying the need for tailored training to bridge confidencegaps. These results have important implications for the adoption of AI tools in science education,emphasizing the need for user-centric design, targeted training programs, and further explorationof long-term adoption trends. This study contributes to the growing body of research on AI ineducation and provides practical recommendations for fostering engagement, equity, andinnovation in science learning.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17736596

Authors: Karafyllidis, Theodoros, Papaevripidou, Marios, Milopoulos, Gregory, Gardelli, Viktor, Katsouros, Vassilis, Simistira Liwicki, Foteini, Mokayed, Hamam, O Murchu, Daithi, Paraskevopoulos, Georgios, Stamouli, Spyridoula, Vacalopoulou, Anna, Zacharia, Zacharias

Institutions: University of Cyprus, Ellinogermaniki Agogi, Luleå University of Technology, Athena Research and Innovation Center In Information Communication & Knowledge Technologies, Institute for Language and Speech Processing

Language: English

Topic: Artificial Intelligence in Education

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7107871007

FWCI:

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