Computers and Education Open最新文献

Current literature suggests that one of the impressive benefits of digital game-based language learning is its potential to create engaging vocabulary learning experiences. However, this literature is dominated by game-play approaches, rather than game-making approaches. Drawing upon constructivist, motivation, dual-coding, and constructionist theories, this study examined elementary English language learners’ vocabulary learning experiences in a game-based learning context and investigated their experience as they built their own games based on their understanding of different non-fiction texts. This mixed-methods case study involved novel use of network analysis to examine student learning, investigate the relationships between various aspects of learner experiences, and evaluate the strengths and weaknesses of the program. Findings indicated that a complex set of interdependencies between enactments of theoretical principles including generativity, agency, tinkering, intrinsic motivation, and contextualized learning lead to enjoyment and powerful language learning experiences. Design principles for future digital game-based language learning include optimizing visual aspects, spending more time on technical skill development, increasing learner agency, and focusing more on generative and joyful learning experiences.

The closure of schools due to COVID-19 disrupted learning routines of thousands of students, resulting in reported performance decreases, especially among lower-performing students. However, some studies on students’ performance within intelligent tutoring systems (ITS) also found significant performance increases for times of school closures as compared to before. However, little is known about students’ longitudinal performance trajectories within ITS. Accordingly, we evaluated longitudinal data from German students (n ≈ 2,700 students; n ≈ 5 million problems) enrolled in an ITS for learning mathematics from January 2017 until the end of May 2021 to investigate the effect of periods of school closures (first and second) on students’ performance within the ITS during, between, and after school closures. We observed significant performance increases for both lower- and higher-performing students during, between, and after COVID-19 related school closures. Importantly, these improvements were more pronounced for lower-performing students compared to higher-performing students. Together, these results suggest that ITS may have helped to maintain mathematics learning, particularly for lower-performing students during COVID-19 related school closures and that these beneficial effects persisted at least for the following months when schools opened again. As such, the use of ITS for learning mathematics seems an appropriate approach for distance learning during times of crisis.

The interest in artificial intelligence (AI) in education has erupted during the last few years, primarily due to technological advances in AI. It is therefore argued that students should learn about AI, although it is debated exactly how it should be applied in education. AI literacy has been suggested as a way of defining competencies for students to acquire to meet a future everyday- and working life with AI. This study argues that researchers and educators need a framework for integrating AI literacy into technological literacy, where the latter is viewed as a multiliteracy. This study thus aims to critically analyse and discuss different components of AI literacy found in the literature in relation to technological literacy. The data consists of five AI literacy frameworks related to three traditions of technological knowledge: technical skills, technological scientific knowledge, and socio-ethical technical understanding. The results show that AI literacy for technology education emphasises technological scientific knowledge (e.g., knowledge about what AI is, how to recognise AI, and systems thinking) and socio-ethical technical understanding (e.g., AI ethics and the role of humans in AI). Technical skills such as programming competencies also appear but are less emphasised. Implications for technology education are also discussed, and a framework for AI literacy for technology education is suggested.

In this paper, we explore how the theoretical notion of possibility space offers a way to study how children's computational thinking develops as a process. Drawing on embodied notions of cognition, we first examine the literature that supports how children's computational thinking emerges as a possibility space that involves conceptualizing possible actions in a given moment, deciding which action to take by anticipating the results of a possible action, and learning from the actions that they have taken. We then use a grounded approach to analyze the problem-solving process of two 5th-grade children who engaged in an educational robotics activity over two 50-minute class periods. The findings lend support for approaching children's computational thinking as a cycle of action-taking that includes conceptualizing, anticipating, and taking action. The findings also support the pedagogical practice of having children predict the results of a computer program to enhance their computational thinking. Implications for the way that teachers can support children in learning to conceptualize what is possible and take action from it are discussed.

Massive Open Online Course (MOOC) integration into campus education is rising, in many different forms. When integrating MOOCs, motivation to learn demands consideration as it is related to academic achievement and well-being. Student motivation in formal integrated MOOC learning is understudied. This study aimed to characterize the shape of motivation to learn in integrated MOOC learning. Motivation profiles of undergraduate students that learn in three different MOOC integration designs were explored, as was the distribution of profiles among integration designs. Finally, factors that underpin motivation were compared between integration designs. Six motivation profiles were recovered through a two-step cluster analysis: Self-determined students, highly self-determined students, grade hunters, and teacher trusters who are moderately, highly, or extremely trusting. Proportions of motivation profiles differed significantly between MOOC integration designs, and psychological needs were satisfied and frustrated significantly different between designs. Implications for future MOOC integration research and practice are discussed.

Over the past decade, learning cultures worldwide have been affected differently by the rapid spread of educational technology. During emergency distance learning, teachers had to adapt themselves to a new mode of learning. The purpose of this study was to compare technology-integrated instructional strategies and teacher prototypes in three learning cultures during routine and emergency learning based on the Five Spaces for Design in Education framework (Weiner et al., 2020). The participants were 31 teachers from three regions - Eastern Europe, Western Europe, and Northern America, all integrating the same adaptive digital learning environment in second language instruction. Participants' interviews were coded according to a three level tier of instructional strategies (n = 938) denoting the student's place in the learning process and level of independence, as well as a categorization of four teacher prototypes representing the degree of teacher centrality in the classroom (n = 764): sage, facilitator, guide, and partner. Chi-square tests highlighted the differences in instructional strategies and teacher centrality between the learning cultures in the three regions. The findings of the teacher prototype analysis showed a similar distribution of prototypes among the three regions, both in routine learning and emergency times. Regarding instructional strategies, each culture showed a unique tendency to specific strategies, while in the transition to emergency learning there was a convergence to strategies with the medium level of teacher control over students and a certain degree of student independence.

This study explored the value of Adaptive Learning Technologies (ALTs) in K-12 education by examining the advantages and challenges these tools create for teaching and learning from the perspectives of stakeholders involved in the use (Teachers), implementation (Teacher Support professionals), and development (EdTech professionals) of ALTs. We conducted qualitative thematic analysis on 25 stakeholder interviews using the Teacher Response Model as a guide for examining stakeholders’ perceptions of the advantages and challenges of ALTs. Analysis resulted in three overarching concepts (i.e., learning management, student agency and engagement, and implementation challenges), under which themes regarding stakeholder perspectives on the advantages and challenges of ALTs could be organized and contrasted with one another. Learning management themes suggest that stakeholders perceive features such as real-time student data and tailored learning content as creating value for teachers by supporting efficiency in their learning management, however that value is impacted by stakeholders’ concerns with ALT grading and data collection processes. Student agency and engagement themes highlight how certain user interaction features can create value or challenges for learners depending on whether the features were designed with students’ developmental and competence needs in mind. Finally, the implementation challenges themes suggest that for ALTs to create value in K-12 settings, stakeholders need better alignment around their ALT implementation goals and expectations. We leverage these data to make recommendations for future research and development so stakeholders can maximize the affordances of ALTs for K-12 students and teachers.

Within the past ten years, the public's use of wearables, such as smartwatches and fitness trackers, has greatly increased. Recently, researchers have published systematic reviews to examine how wearables are used in educational settings. However, not all wearables are alike. Head-mounted wearables and exoskeletons may be viewed as invasive, whereas smartwatches and wristbands are commonly worn by the public. In this scoping review, we systematically review the literature around wrist-worn wearables (WWs) in educational settings. Our systematic search revealed 1,932 unique research items, of which 46 met the inclusion criteria and were analyzed. Our findings reveal the trends in the field, we discuss the vast heterogeneity seen in the field, and we make a call for further in-depth systematic reviews in the areas of WWs as educational interventions, of studies where the data from WWs is used to predict or classify different types of outcomes, and about data privacy, data security, ethics, and legal concerns around WWs in educational settings.

To effectively adopt technology during teaching, teachers require knowledge of how to operate technology. Especially first-time technology users need knowledge of how to handle digital devices and software programs as a foundation to use technology in the classroom successfully. This knowledge has so far been assessed mainly using self-reports. However, self-assessments are insufficient for assessing knowledge as their validity is limited. Moreover, the few tests that exist to measure technological knowledge (TK) show weaknesses (e.g., lack of ecological validity, outdated items). We present a test assessing teachers' TK that is independent of specific operating systems, covers technology that is relevant in everyday teaching, and is grounded in acknowledged psychometric modeling principles. We iteratively developed a test (named T-TK) comprising 26 items, utilizing cognitive testing, expert feedback, and two studies (N_{pilot study} = 268 pre-service and in-service teachers, N_{main study} = 233 in-service teachers) to filter items that did not match in content and were not Rasch conform. T-TK showed a satisfactory Andrich's reliability (Rel_Andrich = 0.73). Using the sample N_{main study}, correlations between T-TK and technological knowledge (self-report, r = 0.52), pedagogical knowledge (test scores, r = 0.18), and technological pedagogical knowledge (self-report, r = 0.33; test scores, r = 0.46) indicated convergent and discriminant validity. Thus, the T-TK proves to be a reliable and valid instrument to capture teachers' TK. The T-TK can be used both by practitioners not requiring any statistical knowledge (e.g., for individual diagnostics) and in research (e.g., to analyze teachers' TK).

The use of digital learning technologies and platforms has skyrocketed over the past decade. Although digital materials have many advantages, using them can be frustrating to students. Frustration is a negative achievement emotion that can serve as a barrier to learning. Therefore, understanding how frustration influences student learning and attitudes toward technology can help create more engaging and effective digital learning experiences. Previous research has identified three areas of frustration with academic e-textbooks (e-text frustration): (1) interactions with e-text interface, (2) technical difficulties, and (3) curriculum integration. This study investigated the relationships among e-text frustration and motivational, cognitive, attitudinal, academic, and demographic factors that impact frustration with e-texts in undergraduate biology classes. Extraneous cognitive load and motivation significantly predicted each of the three frustration constituents. Surprisingly, intrinsic cognitive load failed to predict e-text frustration. This study makes an important contribution to emotion research in education by examining the factors that impact learning in digital settings and emotions. Its implications are relevant for educators, researchers, and developers of digital learning materials and environments.