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In K-12 education, Computational Thinking (CT) has been a trendy issue in mathematics education, but the approach and results of CT + Math are not yet clear enough. This paper systematically reviewed 22 SSCI journal papers from three perspectives: the current status, outcomes, and implications of mathematics and CT integration. Results indicate that: (1) The empirical studies were more inclined to be carried out in primary school; (2) The sample size inversely proportional to the duration, the same as the duration and the learning phase; (3) the integration of mathematics and CT were gradually emerging in kindergartens, while the empirical studies in junior and senior high schools still needs to be improved; (4) The experimental type prioritizes case studies and lacks mixed research; (5) Most research designs employ a variety of measuring instruments but limited in multimodal data; (6) Through the teaching model of plug-in programming, the integration of mathematics and CT was centred on the field of geometry and number operations; and (7) The CT skills involved are mainly Problem decomposition, Pattern recognition, Abstraction, Algorithm design and Debugging. The limitations and future directions are also discussed in this paper.

Robotics Education (RE) is viewed as a tool to narrow the gender gap in STEM fields, especially for promoting girls' learning. As an emerging and potential model in RE, Pair Learning (PL) is different from Individual Learning (IL), which is impacted by many factors. Among them, social factors need to be further explored. Therefore, this study emphasized gender as a key social factor and focused on girls' learning performance in different learning models (IL and PL) and gender pairing patterns (boy-girl and girl-girl), as well as exploring the effective pedagogy for enhancing girls' learning performance in RE. To this end, we conducted a comparison experiment in two classes from the fifth grade in a Chinese primary school. Results indicated that: (a) PL outperforms IL in enhancing girls' learning engagement; (b) PL and IL have the same effect on the girls' learning attitude and robotics works; (c) Mixed-gender pairing is more beneficial for girls to complete robotics works than single-gender pairing; and (d) Mixed-gender pairing and single-gender pairing have the same effects on girls' learning attitudes and engagement. The key findings, possible reasons, and implications for practice are also discussed.

As a human-friendly system, the artificial intelligence (AI) robot is one of the critical applications in promoting precision education. Alongside the call for humanity-oriented applications in education, AI robotsupported precision education has developed into an active field, with increasing literature available. This study aimed to comprehensively analyze directions taken in the past in this research field to interpret a roadmap for future work. By adopting structural topic modeling, the Mann-Kendall trend test, and keyword analysis, we investigated the research topics and their dynamics in the field based on literature collected from Web of Science and Scopus databases up to 2021. Results showed that AI robots and chatbots had been widely used in different subject areas (e.g., early education, STEM education, medical, nursing, and healthcare education, and language education) for promoting collaborative learning, mobile/game-based learning, distance learning, and affective learning. However, a limited practice in developing true human-centered AI (HCAI)-supported educational robots is available. To advance HCAI in education and its application in educational robots for precision education, we suggested involving humans in AI robot design, thinking of individual learners, testing, and understanding the learner-AI robot interaction, taking an HCAI multidisciplinary approach in robot system development, and providing sufficient technical support for instructors during robot implementation.

This study examined the effects of virtual and physical robots (VPR) using in different learning stages (simple session/complex session) in a robotics programming course. A quasi-experimental design was implemented with 84 junior high school students from two classes. One class with 44 students used combination of VPR strategy for learning, whereas the other class with 42 students used only physical robots (the PR strategy) to learn the same content materials. Results showed that no significant difference was found in the students' learning attitude, programming skills, and learning engagement between VPR and PR, while significant difference existed in engineering design ability and cognitive load, no matter in simple or complex learning sessions. Although the VPR strategy is not always better than the PR one, it has unique advantages on facilitating students' higher-order thinking in solving complex problem, as well as reducing their cognitive load. These findings highlight that VPR is more valuable to the engineering design tasks than PR, and indicate a potential direction in the future to integrate Virtual Reality/Augment Reality into robotics education.

One of the aspects of programming that novices often struggle with is the understanding of abstract concepts, such as variables, loops, expressions, and especially Boolean operations. This paper aims to explore the effects of programming tools with different degrees of embodiment on learning Boolean operations in elementary school. To this end, 67 fifth graders were divided into two groups and participated in a 16-week quasi-experiment. The two groups were randomly assigned to two treatments: the Middle Degree of Embodiment class using AS-Block and the High Degree of Embodiment class using Boson Kits. The results indicated that (a) there were no significant differences in learning attitude (p>0.05), learning immersion (p>0.05), compatibility (p>0.05) and cognitive load (p>0.05) between the two groups; and (b) the High Degree of Embodiment class performed significantly better in terms of the quality of programming works (p<0.01, r[subscript G]=0.533) and the final test score (p<0.05, r[subscript G]=0.860) than the Middle Degree of Embodiment class. The experimental results are presented, and their implications for the instruction and development of programming education and embodied learning are addressed.

Background: Although some researchers have applied both cooperation and competition in the practice of robotics education, most of these practices were not systematic, and there was no integration design for intra-group cooperation and inter-group competition. Objectives: The study aims to examine the effects of different coopetition designs on students' intragroup cooperation and intergroup competition. Methods: A two-stage study was conducted in two elementary schools. In the pilot study, two coopetition designs were developed by combining rewarded and unrewarded competition. In the follow-up study, three coopetition designs (i.e., zero-sum with real-time reward, zero-sum with delayed reward, and social-comparison) were examined. Results and Conclusions: The study showed that both social-comparison coopetition and zero-sum real-time reward coopetition can be more effective than zero-sum delayed reward coopetition in teaching knowledge and skills in robotics education. Social comparison coopetition turned out to have a larger effect on affective outcome than the zero-sum delayed reward coopetition. Implications: Social comparison coopetition seems to be a more advantages method for both cognitive and affective learning. However, more research is needed to confirm the difference in effectiveness between the three models of coopetition.

Many countries and regions have reached a consensus to promote science, technology, engineering, and mathematics (STEM) education in the past decade. A body of studies have demonstrated that the design and organization of interdisciplinary teaching activities are important for the effective implementation of STEM education. So far, however, little attention has been paid to the taxonomy of teaching models in STEM education. This paper aims to propose a taxonomy based on the dimensions of learning outcomes (i.e., product-oriented and knowledge-oriented) and teaching process (i.e., forward teaching model and reverse teaching model) in STEM education. Through the intersection of the above two dimensions, four teaching models in STEM education have emerged, including project-based learning (PBL), reverse engineering (RE), scientific inquiry (SI), and troubleshooting/debugging (T/D). In addition, four cases are introduced to explain how these four teaching models operate in STEM education. The implications of this work for future research are also discussed. It is promising that the study will be valuable to enrich the current research, and shed light on the theory and practice of STEM education.

Studies have indicated the importance of scaffolding in the problem-solving process, as well as the potential of integrating learning content into the troubleshooting tasks. However, few have explored in depth the learning process during troubleshooting via scaffolds while also taking students' cognitive load into account. To address this issue, four kinds of scaffolds (with/without process information plus with/without solution) were set up during three learning phases (Introductory, Mastery, Applicable) in a robotics course. A total of 171 seventh graders participated in the course and learned by troubleshooting with different scaffolds. An experiment with 4 × 3 mixed design was employed to evaluate students' troubleshooting performance (higher-order ability), cognitive load and programming skill (lower-order ability). Across the three learning phases, the scaffold with process information while without solution, was always more effective for students' higher-order ability compared to the other scaffolds. However, there was no significant difference in the low-order ability among the four scaffolds in the Applicable Phase. Results confirmed that the expertise-reversal effect of learning scaffold would appear in the students' lower-order ability cultivation, but not the higher-order ability. This is a new finding for deeper insights into learning scaffolds with process information.

Pair learning (PL) in robotics education is derived from pair programming, and impacted by many factors. Two important factors were identified including roles assignment and learning styles in this study. The roles assignment involved Driver-Navigator Pair and Software-Hardware Pair. For the learning style, the dimension of active/reflective was adopted. Therefore, a 2*3 factorial design was employed with the between-subjects factors roles assignment and learning styles. After a one-semester robotics course, we evaluated 66 fifth-grade students' learning achievements, attitude towards robotics, engagement, mental efforts, compatibility, and attitude towards PL. The results indicated that there was no statistically significant difference among different pairs in the above six indicators. Moreover, there was no significant difference in the learning outcomes among pairs of different learning styles. One important explanation is that the joint effect of PL might bridge the difference in learning performance that may be caused by learning style.

In Robotics Education (RE), the hands-on experience with troubleshooting problems is seen as a good catalyst to enhance the participants' problem-solving skills. Based on the pedagogical technique of collaborative learning and pair programming, pair learning is an emerging and potential method in RE, which means that students collaborate in pairs to construct, build, and program a robot under scripted but switchable roles. As a special collaborative learning, can pair learning also improve students' troubleshooting performance in RE? Therefore, we conducted a comparison experiment (pair learning versus individual learning) in two classes at a Robot Summer Camp for high school students. The results indicated that (a) in the process of learning making robot artifacts, students in pair learning group (PLG) had a higher success rate in troubleshooting than that of individual learning group (ILG), but failed in other indicators and (b) in the summative test, the troubleshooting performance of students in PLG was similar with that of ILG. The findings showed that, in terms of troubleshooting, collaborative (pair) learning does not always has the superiority over individual learning in RE, which implicates other factors to be explored in future research. Implications for teaching are also discussed in this exploratory study.

By providing students with a highly interactive and hands-on learning experience, robotics promises to inspire a new generation of mathematical learning. This paper aims to review the empirical evidence on the application of robotics in mathematics education and to define future research perspectives of robot-assisted mathematics education. After a systematic search in online database via keyword search and snowballing approach, we analyzed 20 empirical studies on how to teach and learn mathematical knowledge through robotics. The results indicate that (1) most studies were conducted with a small sample size, the largest research groups were elementary school students and secondary school students, most studies used LEGO robots, robots were primarily applied to teach and/or learn graphics, geometry, and algebra, and almost half of the studies taught mathematics by engaging students in game-like interactions with robots; (2) half of the studies adopted a non-experimental research design, and most studies evaluated student performance through observation, test/examination, questionnaires, or verbal interviews; and (3) instructional implications proposed in the 20 papers can be clustered into four themes: human-robot interaction, connections between mathematics and real life, pedagogical suggestions, and facility conditions. The 20 papers suggest that robotics generally plays an active role in mathematics education; however, there are indeed situations in which no significant improvement was found in students' mathematical learning. In view of this, we prospect the future research perspectives of robot-assisted mathematics education and propose that more rigorous intervention studies could be conducted to further explore the integration of robotics and mathematics education.

Background: Science, technology, reading and writing, engineering, art, and mathematics (STREAM) education is an emerging form of STEM/STEAM education. STEM education research focuses on how students acquire knowledge and skills. The potential of reading and writing to effectively support students in STEM education has been the focus of research. Although researchers have noted the role of language, they have not explored it in depth. Purpose/Hypothesis: This paper presents a systematic review of STREAM education to clarify how reading/writing is integrated with STEM/STEAM education and explores the level of cognitive goals in instruction. Design/Method: By searching for articles related to STREAM education up to 2021, we coded some important features of STREAM education and highlighted the correlations between two or more features. Results: (i) STREAM education has developed rapidly in the past 3 years; (ii) Writing appeared in STEM education before reading, and the trend of research is spreading from college to lower school levels; (iii) The combination of reading and writing is better in primary school and is underemphasized in middle school; (iv) The cognitive goals of STREAM education in higher education are slightly higher overall than those before college; (v) Current studies focus on the reflection process of the course, while the main process deserves more attention; and (vi) reading/writing activities in the reflection process achieved the highest levels of cognition than in the entry and main processes. Conclusion: The integration of language activities (reading and writing) into STREAM education is a trend toward disciplinary integration, which helps develop students' cognition and form knowledge constructs. [ABSTRACT FROM AUTHOR]

In recent years, Game-Based Learning (GBL) has been widely adopted in various educational settings. This paper aims to review empirical studies that adopt GBL in the field of AI education and explore its future research perspectives. After a systematic keyword search in the online database and a snowballing approach, a total of 125 empirical papers with 133 studies were targeted as samples. Results indicated that the games in AI education are mainly fell into five categories: Puzzle games are the most used in the curriculum (27.07%), followed by Reasoning strategy games (23.31%), Robot games (18.05%), Role-playing games (9.02%) and Simulation games (6.77%). Among them, 22.39% of games were with real characters, 11.94% were with virtual characters and 64.18% were with no characters. Besides, games were used in three main forms in AI education: games as teaching tools (78.95%), games as student works (12.03%), and games as a competing mechanism (9.02%). Researchers mainly paid attention to the effect of GBL on students' Opinions and Attitude (52.96%) and Learning achievement (24.04%), while the other three categories such as Skills and ability, Interaction, and Cognition were not extensively measured. The cross-sectional analysis, research gaps, and potential directions for future research were also discussed. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is a fundamental skill for students, and assessment is a critical factor in education. However, there is a lack of effective approaches to CT assessment. Therefore, we designed the Three-Dimensional Integrated Assessment (TDIA) framework in this article. The TDIA has two aims: one was to integrate three dimensions (directionality, openness, and process) into the design of effective assessment tasks; and the other was to assess comprehensively the three dimensions of CT including computational concepts, practices, and perspectives. Guided by the TDIA framework, we designed three pairs of tasks: closed forward tasks and closed reverse tasks, semiopen forward tasks and semiopen reverse tasks, and open tasks with a creative design report and open tasks without a creative design report. To further confirm each task's applicability and its advantages and disadvantages, we conducted a test experiment at the end of the autumn semester in 2014 in a primary school for 3 weeks. The results indicated that (a) the reverse tasks were not more superior than the forward tasks; (b) the semi-open tasks and the open tasks were more effective than the closed tasks, and the semi-open tasks had higher difficulty and discrimination than the others; (c) the self-reports provided a helpful function for learning diagnosis and guidance; (d) the scores had no significant difference between the schoolboys and the schoolgirls in all six tasks; and (e) the six tasks' difficulty and discrimination were all acceptable, and the semi-open tasks had higher difficulty and discrimination than the others. To effectively apply them, the following suggestions for teachers to design computational tasks are proposed: motivating students' interest and enthusiasm, incorporating semi-finished artifacts, involving learning diagnosis and guidance, and including multiple types of tasks in an assessment.

Technology-Based Embodied Learning (TBEL) is a hotspot in learning science. By systematically reviewing 49 SSCI journal articles, this paper revealed the relationship between any two of sample group, sample size, duration, subject distribution, research design, and measurement instrument, etc. In general, the major results showed TBEL is helpful for students to enhance the knowledge comprehension and skills, improve long-term retention and transfer, et al. But sometimes, the effect of embodied learning may be limited by types of learning, age of learners, or redundant strategy. We also derive some limitations and future research directions from reviewed papers. ABSTRACT Technology-Based Embodied Learning (TBEL) has become a hotspot in learning science. This paper systematically reviewed 49 SSCI journal articles. The results mainly indicate that: (1) The learning phase is proportional to sample size; (2) The sample size of experiments is inversely proportional to the duration; (3) The experiment duration may be inversely proportional to the learning phase; (4) The integration between experiments and various subjects in middle and high school still needs to be improved; (5) A variety of measurement tools are used for almost every type of research design; (6) TBEL has been integrated with a variety of embodied learning theories in various disciplines, especially mathematics and language; and (7) Comparing with other interaction modes, tangible interaction is more conducive to achieve a higher degree of embodied learning, et al. In general, the major results showed TBEL is helpful for students to enhance the knowledge comprehension and skills, improve long-term retention and transfer, achieve high levels of engagement and attention, increase positive learning attitude, and decrease cognitive load. But sometimes, the effect of embodied learning may be limited by types of learning, age of learners, or redundant strategy. We also derive some future research directions from reviewed papers. [ABSTRACT FROM AUTHOR]

This study developed a robotic online simulation platform (i.e., IRobotQ3D) for K‐12 education, which realized several main fundamental functions, such as the three‐dimensional (3D) structure design of the robot, a combination of components, graphical programming, and motion simulation. Based on the PhysX physics engine, this system regarded the robot and interactive environment as a rigid body and simplified the robot dynamics, so that ordinary users don't have to care about the complex dynamic problems. In particular, graphical and modular programming modes were adopted, which greatly facilitates the development of robotic learning for K‐12 students. Students can use the IRobotQ3D software on the computer to build virtual robots and simulation environments, write and debug programs to run the operation of physical robots in the simulation window. The technical route of building simulation design function for each physical robot in a 3D environment was determined, and the four‐stage iteration design process was described in detail. Then the steps of applying IRobotQ3D in robotics education were introduced and an experiment was conducted. Forty‐four first‐year junior high school students participated in the experiment. Results indicated that IRobotQ3D plays a positive role in improving students' programming ability, learning attitude, and learning engagement, and demonstrates great educational potential. Finally, the educational value of IRobotQ3D was discussed. [ABSTRACT FROM AUTHOR]

The purpose of the study is to explore the effectiveness of reverse engineering pedagogy (REP) and forward project‐based pedagogy (FPP) in K‐12 robotics education. A two‐stage study was conducted in two secondary schools, involving a total of 169 students. Based on the experience of the pilot study (Study 1), we refined the REP and examined its effectiveness through a quasi‐experimental design in the formal study (Study 2), which included four teaching models: the Deconstruction Recovery Model, Troubleshooting Model, Element Minitrim Model, and Structural Innovation Model. Results indicated that students in the REP group performed significantly better and perceived a higher degree of compatibility and creative self‐efficacy than those in the FPP group, which is consistent with the final robotics product evaluation. However, no significant difference was found in the learning attitude towards the course. The research findings highlight the value of REP in robotics education, especially in cultivating creativity and enhance learning performance, however, it needs reasonable planning and design. [ABSTRACT FROM AUTHOR]