EASE Letters, Volume 2. No. 2. October, 2023
Exploring Students’ Perceptions on Science Learning Emotion and Constructivist Learning Environment
Authors: Shin, Myeong-Kyeong; Kim, Eun-Jeong
Cite as: Shin, M. -K., & Kim, E. -J. (2023). Exploring Students’ Perceptions on Science Learning Emotion and Constructivist Learning Environment. EASE Letters, 2(2), 1-10.
Abstract: The purpose of this study is to analyze students’ perception of science learning emotion and constructivist learning environment. For this aim, the correlation analysis was conducted to figure out the sub-scales of a couple of factors; science learning emotion and constructivist learning environment. The subject of this study were 100 elementary school students. The test tool for science learning emotion consisted of 35 questions, and for constructivist learning environment consisted of 30 questions divided into five sub-scales. The results of this study are as follows. First, most of science learning emotions sub-scales had a positive correlation between positive or negative ones. Secondly there was a statistically significant positive correlation between all five sub-scales of Constructivist Learning Environment Survey.
Keywords: elementary school students; science learning emotion; constructivist learning environment
AI & Digital Competency Elements Necessary for Elementary and Secondary Science Teachers
Authors: Lee, Gyeong-Geon; Shin, Myeong-Kyeong; Lee, Jong-Hyeok
Cite as: Lee, G. -G., Shin, M. -K., & Lee, J. -H. (2023). AI & Digital Competency Elements Necessary for Elementary and Secondary Science Teachers. EASE Letters, 2(2), 11-24.
Abstract: The 21st century, anticipated to bring significant changes to our lives, including educational practices and research, is now characterized by the rapid advancement of Artificial Intelligence (AI). This discourse on AI technology, while overlapping with the existing digital technology discourse, demands a new educational response due to the emergence of intelligent actors. Especially in Korea, there is an ongoing exploration of the future educational landscape for students through AI-integrated education policies. At this juncture, it is essential to reconsider the roles and functions of teachers, the primary stakeholders in Korean elementary and secondary education, to lead new educational practices. Specifically, for AI-integrated education to be effective in classrooms, it is crucial to clarify teacher competencies tailored to specific subjects. This study aimed to derive AI & Digital competency elements necessary for elementary and secondary science teachers. Based on literature reviews, potential AI & Digital competency elements for science teachers were initially identified, along with corresponding behavioral characteristics. Subsequently, an extended expert panel consisting of 37 educational and subject education experts and a Delphi survey involving 10 science education experts were conducted to refine these elements. The final AI & Digital competency elements for science teachers, presented after an expert consultation, were detailed into 16 elements across three major domains. The significance of this study lies in its derivation of AI & Digital competency elements tailored to the unique educational practices of science subjects.
Keywords: Artificial Intelligence (AI), Digital Literacy, Technological Pedagogical Content Knowledge, Science Education, Teacher Competency
Statistical Validation of Remote Laboratory Perception Survey (RLPS) for University Students
Authors: Gyeong-Geon Lee
Cite as: Gyeong-Geon Lee (2022). Statistical Validation of Remote Laboratory Perception Survey (RLPS) for University Students. EASE Letters, 2(2), 25-34.
Abstract: A hands-on laboratory course is one of the essentials in university STEM education. However, the COVID-19 pandemic in 2020 has changed global STEM education practices into the non-face-to-face format, forcing university instructors to implement and students to take remote laboratory courses. Lee et al. (2023) developed the Remote Laboratory Perception Survey (RLPS) to investigate university students’ perception of remote laboratory courses they took in 2020 and elicit effective teaching strategies for remote labs. However, there is a need for the statistical validation of RLPS if it is to be used in future studies. This study statistically validated RLPS based on internal reliability (Cronbach’s α) and confirmatory factor analysis (CFA) results based on 291 university student responses. The structure of RLPS, which consists of 10 factors with 30 items, was validated to have good internal reliability and fit indices in CFA. The result of this study suggests that the RLPS is a plausible instrument to investigate and report university students’ perceptions of remote labs.
Keywords: university STEM education, laboratory courses, remote laboratory perception survey (RLPS), statistical validation