Previous studies measured flow states using students’ self-reported experiences, resulting in issues regarding nonobjective and nonreal-time data. Thus, this study used an electroencephalogram (EEG) to measure the EEG-detected real-time flow states (EEG-Fs) of 30 students from the 4th and 5th grades. Their EEG measurements, self-reported reflective flow experiences (SR-Fs), grade levels (GLs), balance of challenge and skill (BCS), and sense of control, represented by their overall test performance (OA-tp) and momentary test performance (MOM-tp), were analyzed to establish their EEG-F’s construct. Based on the results of a chi-square test, the EEG-F correlates significantly with SR-F, BCS, OA-tp, and MOM-tp. A J48 decision tree analysis and logistic regression further revealed that in-flow experiences (in-EEG-F) were detected when students had high SR-Fs, where the BCS contributed to flow states. In particular, students with a low-challenge/high-skill BCS demonstrated an in-EEG-F state upon having a high OA-tp. For high-challenge/high-skill, the in-EEG-F state was determined through their MOM-tp. Through the EEG and flow state construct, this study revealed a whole-part association between students’ momentary and overall reflective flow experiences and identified viable paths for inducing students’ EEG-Fs, which can contribute to future e-learning development when integrated with a brain-computer interface for e-learning or e-evaluation systems.

As game-based learning continues to draw attention, students’ perceptions toward classroom activities are vital in influencing the quality of learning. This study used the social cognitive theory to show the perception traits of learning and playing in game-based environments and for students to identify their self-efficacy toward game-based learning by different trait groups. The game Formosa Hope was used in an experiment with 362 fifth- and sixth-grade students at ages 11 to 12 years as participants. Three perception traits were identified through a two-step cluster analysis: I—strong perceptions of learning and playing, II—moderate perceptions of learning and playing, and III—strong perception of playing but weak perception of learning. This study showed that regardless of trait type, students demonstrated positive self-efficacy, with those with Trait I having significantly higher self-efficacy than those with Traits II and III, indicating that students’ positive perceptions of learning and playing are essential in prompting self-efficacy in game-based learning.

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Studies have shown that although traditional instruction is effective in developing students' conceptual understanding, it lacks in strengthening their thinking skills. To enhance traditional instruction and establish an approach using game-based instruction, this study developed Multi-genre digital Gamebased Instruction (MGI), which integrates various game genres-situated and competitive-with traditional instruction. A total of 115 fourth-graders (9-10 years old) of 4 classes participated in the study, of which 2 classes made up the MGI (experimental) group and the other 2, the traditional instruction (control) group. Quantitative and qualitative data were collected to answer research questions by examining the comparative effectiveness of the two groups separately as well as the effectiveness by achievement level, and exploring students' learning experiences. Findings showed that using MGI resulted in a significant improvement in conceptual understanding and argumentation skills compared to those who were taught only with traditional instruction. Furthermore, it showed that MGI was significantly more effective than traditional instruction in improving low-achieving students' conceptual understanding, as well as improving argumentation skills for all achievement levels. Students' learning experiences with MGI showed how the proposed instruction is superior compared to existing traditional instruction.

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This study gathers and examines information about the flow state’s emergence during tests and its factors using an electroencephalogram (EEG) to establish a method and reveal an individual student’s flow construct. Through a single-case experimental design and 766 test items, multiple measurements were performed on a 14-year-old junior high school science-gifted student. During the test, self-efficacy, item difficulty, cognitive load, and test performance (long-term test performance [LT-tp] and short-term test performance [ST-tp]) were examined to establish the construct of EEG-detected, real-time flow states (EEG-Fs). Based on the chi-square test of independence results, the EEG-F had a significant correlation with the student’s cognitive load, self-efficacy, LT-tp, and item difficulty. Furthermore, a J48 decision tree analysis and logistic regression revealed four inhibiting and two inducing conditions affecting the emergence of EEG-Fs. The two inducing conditions included (1) high self-efficacy with a low cognitive load (odds ratio (OR) = 3.7) and (2) high cognitive load when combined with high self-efficacy and LT-tp for low-difficulty items (OR = 3.5). The established method and findings may help teaching designers or automated teaching applications detect the individual student’s flow construct to select appropriate test tasks accordingly, resulting in an optimal experience and better achievements.

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The use of scientific models has been regarded as an important skill for scientific enquiry. However, although many national curricula and major international science education reform movements have stressed the use of scientific models in science teaching and learning, students and teachers generally do not know how to perceive models properly. This research explores these perceptions about scientific models using the Perception of Models in Science (PMS), a self-developed instrument designed to collect participants’ model perceptions, among 218 grade 4, 6 and 8 students, as including 57 of the science teachers in their respective schools, and treated these statistically with analysis of variance, post hoc analysis and cluster analysis. Results showed that the groups of students and teachers agreed that the most acceptable model representation is reality but remained uncertain on whether a model can be presented through nonreality representations (i.e., diagram, graph, symbol, writing and speech). Participants did not significantly differ in perception intensity of seeing each model representation and held three kinds of model perceptions: daily language, transitional and scientific language. This research thus proposes action plans in managing this transitional perspective in learning the concepts of scientific models. Keywords: model representations, scientific model, students’ view, teachers’ view