1,720,958 research outputs found
The effects of peer instruction through social learning environment towards students’ cognitive load and learning performance
Full text linkThe use of social media like Facebook as an educational tool has been reported to be able to promote learning and serve as a learning platform. However, Facebook also contributes to promote increased mental demand or Cognitive Load (CL). It is a challenge to learning due to the limitation of the working memory for information processing can have effects on learning performance. This situation has not been well emphasized by most instructors. Studies reported that Peer Instruction (PI) learning strategy has the potential to reduce CL while also improving learning performance but implementation of PI in social media is rather new. Thus, this study focuses on the development of a framework for best practices on the use of social media for education through enhancing learning performance and reducing CL using PI. A two-phase study was implemented for this purpose where Phase 1 involved a survey to 226 students at a Malaysian public university to identify students’ experience of CL during learning on social media. Findings confirm that students experience distractions during learning on Facebook with third party activities identified as the most distracting. Phase 2 was a mixed method study design involving a purposeful sample of 12 postgraduate students who underwent learning with Facebook. This study investigates the effect of PI for enhancing learning performance and reducing CL. Wilcoxon signed-rank test showed a significant reduction in students CL (p < 0.05) with a corresponding significant improvement in learning performance (p < 0.05) when PI was employed as an instructional strategy. A qualitative study involved collection of student reflections, participation data in whole class discussions and data from a focus group session were analysed using NVivo 10 CAQDAS software to aid the coding process. Findings showed CL sources on learning with social media include mental, time and affective demands. PI was found to bring about the reduction of CL through the following elements; ConcepTests, voting, peer discussion and mediated pre-class reading. A modified framework of PI implementation was developed that incorporates online mode, whole-class peer discussions in pre-class and post-class settings, pre-class ConcepTests, voting and mediated pre-class reading as means to reduce cognitive load. It highlights how the advantages of social media can be optimized. Findings from the study have implications for curriculum and instructional design and how it can support learning by reducing CL through PI
Reimagining Transformative Educational SpacesTechnological Synergy for Future Education
No full textThis book explores the symbiotic relationship between human learning and machine learning, examining how emerging technologies and human-machine interfaces are reshaping the educational landscape
Impact of AI Software on Improving Learning Outcomes and Attitudes of Music Students in Chinese Vocational Schools
Full text linkThis study focused on the application of AI tools in vocational music education. The objective is to determine whether the use of AI tools can help improve music listening and reading skills, thereby helping to address the challenges of access to quality music education by students in poor districts with limited access to learning resources. In a within-subjects experimental procedure involving 44 vocational school students (22 male, 22 female) aged 14-17, participants underwent 3 weeks of learning music listening and reading without technology support (condition 1) and learning with AI support (condition 2). Kimi Assistant AI tool was employed for teaching music listening while Music notation software (Laiyinzhipu) was employed for teaching music reading. Students were tested for both learning and attitude. Three (3) hypotheses were also tested to assess the impact of AI tools on music listening, reading and students’ attitudes. Findings show that using AI software specifically promoted only Melody and Structure indicators in listening skills whereas all the reading skills show marked improvement with AI tool. The implication of this is that AI software might hold more effectiveness regarding the teaching of reading skills. A significant improvement in attitude was also noted with the use of AI tools. However, more in-depth studies are needed to confirm if there are clear correlations between learning outcomes and attitudes with the use of AI software can help students improve their motivation to learn. The study is novel in its focus on music education. The study further shows that a combination of AI software and teacher-led instruction will be more significantly beneficial to students for learning music courses. Recommendations for future studies address the limitations of the study including the short experimental period, software restriction issues, an exploration of learners’ motivation, and studies adopting other designs including surveys and other experimental methods
Emerging technologies for next generation learning spaces
No full textThis book discusses the development of the next generation learning spaces with emerging technologies. These spaces result from the combined needs of classroom stakeholders, such as instructors and learners, with classroom elements, such as tools and technologies, pedagogy and content. The book presents discussions and studies on issues, possibilities and implications of these changes for next generation education. Novel ideas, and studies on these all-encompassing, blended roles of technologies in next generation learning spaces are clearly presented. Suggestions on how the benefits they offer can be maximized are also discussed. Engaging learning technologies have remained central in education for assisting instructors to teach and learners to learn, more effectively. However, recent technological growth is creating a system in which previous divides between key classroom concepts and stakeholders are getting progressively blurred. This is giving rise to next generation learning spaces where elements and stakeholders are blended into one. The book addresses the future of learning environments based on these perspectives
Facilitating Cognitive Load Management and Improved Learning Outcomes and Attitudes in Middle School Technology and Vocational Education Through AI Chatbot
Full text linkJunior Secondary School (JSS) or middle school education is peculiar as it involves the introduction of a wide array of subjects across the sciences, arts, humanities, business and vocational fields to young learners. This situation can be ovewhelming, resulting in high cognitive load (CL), with consequent poor learning outcomes, and other negative issues including high dropout rates, requiring urgent attention. AI tools have been explored for addressing multiple learning issues. AI chatbots are particularly useful based on their ability to support individualized learning, pre-training, and other concepts that can facilitate CL management. This study evaluated the impact of an AI-based chatbot system for reducing students’ CL and improving learning outcomes, attitude and retention among JSS students. A quasi-experimental study with 120 students was conducted over an 8 week period with 24 learning sessions. The experimental group (N=60) learnt using ‘iLearnTech’, an AI Chatbot developed specifically for the study. The control group (N=60) learnt through the traditional approach with no chatbot. Learning content was based on the JSS Basic Technology education, a precursor to TVET. Data was collected using the Cognitive Load Measure, the Basic Technology Achievement Test, Students’ Attitude Survey (SAS), and Students’ Retention Test. The experimental group exhibited huge reductions in CL and corresponding improvements in learning outcomes, attitude and retention. The results also confirmed known relationship between the dependent variables and highlights the potential of AI powered educational tools for addressing diverse educational issues including promoting equitable access, and sustainable education in developing nations and resource-constrained environments. This work contributes to ongoing discussions on AI applications in education. Its novelty lies in its exploration of AI technology in addressing CL issues in the context of junior secondary education. Implications for educational policy and practice, particularly curriculum design and e-learning integration are highlighted
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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