Education and Information Technologies最新文献

MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion rates. While existing research primarily focuses on identifying urgent posts through various classification techniques, it has not adequately addressed the underlying reasons behind them. This research aims to delve into these reasons and assess the extent to which they vary. By understanding the root causes of urgency, instructors can effectively address these issues and provide appropriate support and solutions. BERTopic utilizes the advanced language capabilities of transformer models and represents an advanced approach in topic modeling. In this study, a comparison was conducted to evaluate the performance of BERTopic in topic modeling on MOOCs discussion forums, alongside traditional topic models such as LDA, LSI, and NMF. The experimental results revealed that the NMF and BERTopic models outperformed the other models. Specifically, the NMF model demonstrated superior performance when a lower number of topics was required, whereas the BERTopic model excelled in generating topics with higher coherence when a larger number of topics was needed.The results considering all urgent posts from the dataset were as follows: Optimal number of topics is 6 for NMF and 50 for BERTopic; coherence scores is 0.66 for NMF and 0.616 for BERTopic; and IRBO scores is 1 for both models. This highlights the BERTopic model capability to distinguish and extract diverse topics comprehensively and coherently, aiding in the identification of various reasons behind MOOC Forum posts.

Middle school students often enter Computer Science (CS) classes without previous CS or Computational Thinking (CT) instruction. This study evaluated how Code.org’s block-based programming curriculum affects middle school students’ CT skills and attitudes toward CT and CS. Sixteen students participated in the study. This was a mixed methods action research study that used pre- and post-tests, surveys, artifacts, and interviews as data sources. Descriptive statistics, paired samples t-tests, and inductive thematic analysis were administered. Findings showed a statistically significant increase in participants’ algorithmic thinking, debugging, and pattern recognition skills but not in abstraction skills. Attitudes toward CT and CS improved but the difference was not statistically significant. Qualitative themes revealed benefits of game-based learning to promote CT skills, collaboration to promote successful error debugging, and enjoyment of programming resulting from a balance between structured guidance and creative freedom. Findings emphasize the importance of low-threshold and engaging strategies to introduce novice learners to CT and CS.

While GeoGebra applets have been extensively investigated in learning environments, few studies have addressed the interactive GeoGebra applets in an e-book-based learning environment. This study aims to compare the effects of the e-book created with interactive GeoGebra applets on students’ learning achievement and motivation. The sample of the study consisted of 67 sophomore students attending the same class in the mathematics undergraduate program of a state university. All participants were randomly assigned to an experimental group and a control group. The students in the experimental group used the interactive GeoGebra applets embedded in the e-book, while those in the control group used the static PDF e-book. The results revealed that the e-book with GeoGebra applets could exert a significantly better impact on the students’ learning and motivation than the static PDF e-book use. Moreover, MANCOVA and post hoc comparisons indicated that the students who used e-book with GeoGebra applets showed a significantly higher level of motivation in the dimensions of attention-relevance and confidence-satisfaction than those who used static PDF e-book. According to the results, interactive GeoGebra applets can be easily adapted to the e-book environment. Therefore, this study may suggest that we should make effective use of existing technologies rather than reform innovations when designing e-books. The implications of the educational practice are discussed, and the direction of future studies in this field is also addressed.

Feedback plays an indispensable role in pre-service teachers’ microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly capable of delivering feedback on microteaching performance. Yet, the effects of differing feedback types on the microteaching practices of pre-service teachers are not well documented. This study examines the impact of three types of feedback—observation-based, teaching analytics-based, and combined (a combination of both)—on pre-service teachers’ microteaching performance, scope of reflection, perceived usefulness, and satisfaction through an experimental research design. Sixty-five pre-service teachers voluntarily participated and were randomly assigned to three groups: observation-based feedback (N = 21), teaching analytics-based feedback (N = 23), and combined feedback (N = 21). The findings indicate that combined feedback was most effective in enhancing pre-service teachers’ scope of teaching reflection, perceived usefulness of feedback, and satisfaction, but not on microteaching performance. However, when only teaching analytics-based feedback was provided, pre-service teachers perceived it as least useful and were least satisfied. The study discusses the implications of different types of feedback in teacher education.

Augmented Reality (AR) technologies allow for holograms to be layered over the real-world, “augmenting” human vision by adding technical information or illustrations onto 3D space. Although AR-based applications are showing positive effects in many systematic reviews and meta-analyses, well-designed, rigorous studies with strong control conditions are lacking. Further, many experimental studies lack process data to illuminate what is happening as students engage with AR. In this pre-registered study, we conducted an experiment where n = 120 high school students were assigned to reason about identical geometry simulations collaboratively either using tablets or AR head‐mounted displays (HMDs). We look at their learning and how it was impacted by the dimensionality (2D or 3D) of the shapes they explored, as well as how they engaged with virtual objects using gestures and epistemic actions. AR HMDs were more effective for students getting an initial sense of 3D shapes, but less effective for 2D shapes. For gaining insights into the workings of shapes and formulating justifications of conjectures, we see no evidence AR is more effective, and trends indicating AR may be detrimental to eliciting generalizations. Further, process data showed that students using tablets are more likely to manipulate the geometric shapes in the simulations, while students using the AR HMDs are more likely to use dynamic gestures that simulate these manipulations, which are less constrained by the objects’ actual properties. Implications for the future design and use of AR in education are given.

Mathematical literacy is becoming increasingly important and needs to be developed. However, various factors can affect students with different mathematical literacy patterns. This study aims to investigate the effects of students’ backgrounds, attitudes toward mathematics, and information and communication technology (ICT) familiarity on the mathematical literacy of different patterns of students. The data of 15,478 secondary school students from Hong Kong, Macau, and Taiwan in China, who participated in the Programme for International Student Assessment (PISA) 2022 was analyzed. It was found that students’ mathematical literacy can be classified into four clusters: low, medium, moderately high, and high mathematical literacy. In addition, students’ personal backgrounds, attitudes toward mathematics learning, and ICT familiarity can jointly predict mathematical literacy in different clusters. Students’ economic, social, and cultural status (ESCS), self-efficacy toward formal and applied mathematics, and use of ICT outside the classroom for school activities are positive predictors common to all four clusters. Meanwhile, the other variables have mixed predictive effects on different clusters.

This study adopted a framework based on social cognitive theory to explore the influence of thinking styles on critical thinking and multiple mediation effects of student assessors’ assessment performance (scoring and review comments) between them. Samples were 97 graduate students enrolled in the “Seminar” course at a university. Students used an online assessment system and the evaluation form to conduct peer assessments for peers’ reports. Findings revealed: (1) thinking styles primarily had an indirect effect on critical thinking solely through comment performance (complete mediation effect), and it indirectly influenced critical thinking serially through scoring performance and comment performance (completely serial mediation effect), but it cannot solely influence critical thinking through scoring performance. (2) thinking styles directly influenced both scoring and comment performance, and also indirectly affected comment performance through scoring performance (partial mediation effect). (3) scoring performance indirectly influenced critical thinking through comment performance (complete mediation effect), while comment performance directly influenced critical thinking. (4) scoring performance directly influenced comment performance. The main contribution of this study lies in proposing and validating a multiple mediation model of “Thinking Style-Online Assessment Performance-Critical Thinking”, indicating that student assessors’ online assessment performance (scoring and comment performance) has multiple mediation effects between thinking styles and critical thinking. This result holds significant academic and practical implications.

The rapid advancement of educational technologies worldwide and the ubiquitousness of technology-integrated teaching and learning have posed great challenges to teachers. Technology leadership is an emerging focus among educators, it involves using technologies to lead learners’ knowledge, abilities, and values development. However, there are few available scales that can evaluate its level among teachers in China. We proposed a model based on the new version of the ISTE Standard for Educators and addressed a set of indicators. This study developed and validated a 24-item teachers’ technology leadership scale (TTLS) through theoretical review, expert advice, exploratory factor analysis, and confirmatory factor analysis. This study reports the results through analysis of responses from 604 Chinese university students. Our findings revealed good reliability and validity in the scale but demonstrated a three-construct model that differs from the original seven-dimension framework, thus highlighting the characteristics of the Chinese context. This study contributes to a growing body of research that aims to provide researchers, educators, and policymakers with a tool (TTLS) that can be used as a reliable assessment scale for measuring teachers’ level of technology leadership, thus supporting their development in three domains regarding leadership, technology integration ability, and digital responsibility.

Clicker-integrated instruction is the current innovation in teaching and learning. Several studies used this technology to investigate learning processes, while others mainly used it to asses for learning, facilitation of group discussion and students’ participation. All applications require creativity and analytical thinking and very much different from conventional instruction where learning is direct and sometimes unreceptive. However, most of those studies either conducted a meta-analysis of the literature or an intervention with a small group to evaluate its impact on teaching and learning. However, the relationship that exists between its integration through intervention and final regional examination results in chemistry was limited in studies. Therefore, the main focus of the present study was to examine the relationship between an intervention and regional examination results. Data collected and analysed were the 2593 students’ final chemistry results, between grade levels 1 to 6, as the main requirement for university admission. The scope of the data collected from 2017 to 2019. There were 1463 male (56.4%), and 1130 female (43,6%) from the total sample. The findings obtained were compared within and to the findings generated from an intervention, for any relationship. Regression results indicated no relationship between the two findings. Further, multiple regression also suggests that the relative contribution of the clicker technology, stands on firm empirical ground, as it explained 3.5% of the variance in results, which implied that clicker-integrated instruction can be encouraged.

In examining the nexus between education and income levels in rural areas amid contemporary challenges, this article reveals the critical role of education in addressing issues of accessibility and quality in these regions. Utilizing an experimental design with 116 participants in rural China, the study introduced a novel teaching approach to the experimental group, resulting in significant enhancements in educational competence compared to the control group. Statistical analyses, including ANCOVA and t-test, demonstrated a substantial increase in economic development in the experimental group, affirming a positive correlation between education and income levels in rural areas. The study’s practical significance lies in providing specific information and statistical support for an experimental educational program’s efficacy in rural settings, with over 80% of participants praising its quality. The findings underscore the potential of improving education as a key driver in mitigating socio-economic inequalities in rural communities. Future research could explore the long-term effects of such programs and compare their effectiveness across diverse population groups, while also considering additional factors like healthcare accessibility and infrastructure development.