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Research has addressed the benefits of immersive virtual reality (IVR) for affective learning rather than cognitive performance, indicating the necessity to explore what factors may influence learners’ attitudinal learning, defined as the result of instruction for changing learners’ attitudes, when engaging in immersive instructional mediums. This study proposes an affection-oriented model to understand the roles of young learners’ epistemic curiosity traits and triggered situational interest in their attitudinal learning from the affective, cognitive, and behavioral dimensions in IVR learning contexts. Through a series of PLS-SEM analyses with 90 elementary school students, the results of the measurement model test have verified the reliability and validity of the instruments employed in this study. The structural relationships among epistemic curiosity, situational interest, and attitudinal learning were also confirmed. The triggered situational interests of novelty and exploration intention during the IVR learning process were further identified as the mediators in the research model. While the students’ senses of novelty mediated the relationship between curiosity and cognitive attitudinal learning, their senses of interest in exploration intention mediated both the relationships between curiosity and affective attitudinal learning and between curiosity and behavioral attitudinal learning. This study contributed to establishing the theoretical framework for affection-oriented IVR learning.

A prior study developed the Computational Thinking Scale (CTS) for assessing individuals’ computational thinking dispositions in five dimensions: decomposition, abstraction, algorithmic thinking, evaluation, and generalization. This study proposed the Developmental Model of Computational Thinking through validating the structural relationships among the five factors of the CTS. To examine the model, a questionnaire including the CTS was administered to 472 middle school students. A confirmatory factor analysis was used to confirm the construct of the measurements, and a PLS-SEM analysis was used to validate the structural relationships among the factors. The results confirmed that the 19-item CTS has good item reliability, internal consistency, and construct reliability for measuring computational thinking (CT). In the Developmental Model of CT, decomposition and abstraction significantly predict all other three CT dispositions, suggesting that they are the two fundamental factors required for CT development. Moreover, a significant linear prediction path was shown starting from algorithmic thinking, evaluation, until generalization. Thus, a multi-level model was confirmed for the conceptual framework of CT. This model suggests a possible sequence for CT development which may provide a guideline for the teaching objectives of CT for different learning stages in different school levels. Decomposition and abstraction are especially suggested to be emphasized in school curricula before teaching algorithmic thinking or algorithm designs.

The purpose of this study was to understand how students engage in computer-supported modeling-based activities (CSMBAs), and the relationship between their engagement and their modeling competence. Different facets of learning engagement were measured through multiple data, including performance on modeling tasks, self-reported level of engagement, and online behavior patterns of science modeling. The research participants were 76 11th-grade students in Taiwan. The research instruments included online student worksheets, an engagement questionnaire, computer logs, and modeling competence tests. Students’ online worksheets were scored and used to group them into three performance groups—the low-level-performance group (LPG), the middle-level-performance group (MPG) and the high-level-performance group (HPG). ANOVA statistics lag sequential analysis (LSA), and ANCOVA statistics were used for the data analysis. The results showed that, first, in analyzing the engagement questionnaires, students’ negative cognitive engagement, negative behavioral engagement, and negative social engagement all played important roles in their low performance in the CSMBAs. Second, through the use of LSA, it was found that the LPG students lacked evaluative behavior, while the HPG students emphasized reflective behavior. Third, analysis of the students’ pre- and post-modeling competence tests showed that those who were in the HPG and MPG scored significantly higher than those in the LPG in two dimensions of the modeling competence post-tests. The results indicate that efforts made in completing tasks in CSMBAs can lead to better modeling competence. Implications for developing future CSMBAs and for promoting student engagement are suggested.

The aim of the study was to investigate students’ views of model evaluation through the lens of personal epistemology. We developed an integrated analytical framework by combining a developmental framework, including absolutist, multiplist, and evaluatist, with a multi-dimensional framework, including limits of knowing, certainty of knowing, and criteria of knowing. Furthermore, we examined the potential influence of the question contexts and the students’ grade levels. A total of 188 secondary school students were surveyed. Students answered two sets of model evaluation questions based on two scientific contexts. After reading the information about the two models, the students had to choose from three epistemic assumptions and then provide written justifications explaining their choice of assumptions. Quantitative and qualitative analyses were conducted for the multiple-choice questions and the written responses. In both contexts there were higher percentages of 11th-grade students choosing the evaluatist assumptions than the eighth-grade students. For students choosing multiplist and evaluatist assumptions, the 11th-grade students were more likely than the eighth-grade students to think in terms of pragmatic and evidential criteria as the criteria of knowing. Different contexts of the questions evoked different views of model evaluation particularly regarding the limits of knowing. Four additional categories of epistemic levels also emerged from the data. This study provides a new framework for understanding students’ thinking about model evaluation. Implications and suggestions for future research are provided.

Intercity railway system operation on national holidays can be challenging because of possible surging demand. This study proposes an analysis framework to investigate railway system ridership data on national holidays, seeking to attain better understanding of relevant intercity trip patterns, so as to enable enhanced preparation and response before and during national holidays. The ridership data are analyzed in the form of Origin–Destination (O-D) tables and regarded as pictures of N × N pixels, where N is the number of the considered stations/cities in a railway system. The framework primarily adopts a deep auto-encoder to process these pictures to reduce data dimensions and abstracting key features within these pictorial data. Based on the abstracted features, k-means clustering is then conducted to categorize the O-D tables with similar trip patterns into the same group. Further, a discrete outcome model based on logistic regression is developed on the clustering results to enhance the interpretation of the trip pattern in each group and identify the significant holiday-related characteristics and external factors that can affect the trip pattern generation. The ridership data of Taiwan Railways Administration associated with 38 national holidays from January 2014 to August 2018 are analyzed. The analysis results highlight insightful interpretation in relation to clustered trip patterns and relevant trip characterization relative to various national holidays. The proposed framework and developed discrete outcome model are also validated, showing 85% correct assignments of O-D tables to the groups of relevant trip patterns.

In this study, we reviewed 76 journal articles on employing drawing assessment as a research tool in science education. Findings from the systematic review suggest four justifications for using dra...

The purpose of this study was to develop and validate an online contextualized test for assessing students’ understanding of epistemic knowledge of science. In addition, how students’ understanding of epistemic knowledge of science interacts with learner factors, including time spent on science learning, interest, self-efficacy, and gender, was also explored. The participants were 489 senior high school students (244 males and 245 females) from eight different schools in Taiwan. Based on the result of an extensive literature review, we first identified six factors of epistemic knowledge of science, such as status of scientific knowledge, the nature of scientific enterprise, measurement in science, and so on. An online test was then created for assessing students’ understanding of the epistemic knowledge of science. Also, a learner-factor survey was developed by adopting previous PISA survey items to measure the abovementioned learner factors. The results of this study show that; (1) by factor analysis, the six factors of epistemic knowledge of science could be grouped into two dimensions which reflect the nature of scientific knowledge and knowing in science, respectively; (2) there was a gender difference in the participants’ understanding of the epistemic knowledge of science; and (3) students’ interest in science learning and the time spent on science learning were positively correlated to their understanding of the epistemic knowledge of science.

Anti-reflection based on the mimicking of moth eye subwavelength structures (SWSs) has several advantages over conventionally used multilayer thin film antireflective coatings like broad angular and spectral responses, polarization insensitivity and improved stability. In this study, we present the low cost fabrication of moth eye based SWSs on flexible polyethylene terephthalate (PET) substrates using roll-to-roll ultraviolet nanoimprint lithography. We have used a novel method to create a roller mold with embedded nanopores that can be used for easy replication of SWSs without demolding issues. Pure aluminum foil was wrapped around an acrylic cylinder (O = 90 mm) and a multistep anodizing and pore widening scheme was employed to create well-ordered and periodic anodized aluminum oxide (AAO) nanopores with different aspect ratios. Optical characterization of the antireflective PET film shows a transmittance over 92%, an increase of 3% as compared to bare PET, while reflectance can be reduced from 5.3 to 0.09% in the range of visible light. It was observed that higher aspect ratio SWSs is more effective in reducing reflections at higher incident angles. Consequently, we have demonstrated an economically feasible method for fabricating large area polymer films that can be used to reduce light reflections which impose severe limitations on the performance of many optoelectronic devices like solar cells, photodetectors and flat display panels.

This study investigated the relationships among college students’ epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely ‘multiple-source,’ ‘uncertainty,’ ‘development,’ and ‘justification.’ COLB is further divided into ‘constructivist’ and ‘reproductive’ conceptions, while SLB represents deep strategies and surface learning strategies. Questionnaire responses were gathered from 303 college students. The results of the confirmatory factor analysis and structural equation modelling showed acceptable model fits. Mediation testing further revealed two paths with complete mediation. In sum, students’ epistemic beliefs of ‘uncertainty’ and ‘justification’ in biology were statistically significant in explaining the constructivist and reproductive COLB, respectively; and ‘uncertainty’ was statistically significant in explaining the deep SLB as well. The results of mediation testing further revealed that ‘u...

The author of this paper explored Vivaldi [1] [2] line theory and technology and used it as a basis to propose a Vivaldi antenna array to replace a single Vivaldi antenna. This was to achieve a dual-polarized antenna with high directivity and high isolation in the MIMO anechoic chamber, and one that is minimally affected by the environment. The operating frequency of this antenna array covers a frequency range of 0.7–6.0 GHz and is composed of four Vivaldi units with relatively high isolation between them to reduce measurement errors caused by coupling. In each unit, two identical Vivaldi antennas are connected in parallel to form the same polarization unit, and a microstrip power divider was used and the impedance matching of circular holes was performed to design this connected antenna with an ultra-wide operating frequency and the same polarization. The authors then interconnected two polarization units orthogonally at 90 degree cross to form the antenna described in this study, which has high directivity, high isolation, an ultra-wide frequency and dual polarization. During the design process, an FR4 printed circuit board (PCB) was used to effectively reduce the cross-sectional area of the antenna and reduce reflection and interference on the basis of ensuring an ultra-wide operating frequency. Additionally, the two orthogonal units of each polarized antenna unit had to work separately, and the electric field data collected from different polarization directions were sequentially transmitted to the receiver for postprocessing to satisfy the measurement requirements of the MIMO OTA anechoic chamber. In this study, SEMCAD electromagnetic simulation software was used to adjust and complete the analysis of antenna characteristics and obtain a favorable operating frequency and voltage standing wave ratio, as well as excellent isolation and radiation characteristics.

This study aims to disclose how eye-tracking technology has been applied to studies of learning, and what eye movement measures have been used for investigations by reviewing studies that have employed the eye-tracking approach. A total of 81 papers including 113 studies were selected from the Social Sciences Citation Index database from 2000 to 2012. Content analysis showed that eye movements and learning were studied under the following seven themes: patterns of information processing, effects of instructional design, reexamination of existing theories, individual differences, effects of learning strategies, patterns of decision making, and conceptual development. As for eye-tracking measurements, the most often used indices were temporal measures, followed by count and spatial measures, although the choice of measures was often motivated by the specific research question. Research development trends show that the use of the eye-tracking method has proliferated recently. This study concludes that the eye-tracking method provides a promising channel for educational researchers to connect learning outcomes to cognitive processes.