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The authors offer useful information and guidelines for selecting, designing, and developing asynchronous and synchronous e-Learning courses that build knowledge and skills for workers learning in corporate, government, and academic settings.

The essential e-learning design manual, updated with the latest research, design principles, and examplese-Learning and the Science of Instructionis the ultimate handbook for evidence-based e-learning design. Since the first edition of this book, e-learning has grown to account for at least 40% of all training delivery media. However, digital courses often fail to reach their potential for learning effectiveness and efficiency. This guide provides research-based guidelines on how best to present content with text, graphics, and audio as well as the conditions under which those guidelines are most effective. This updated fourth edition describes the guidelines, psychology, and applications for ways to improve learning through personalization techniques, coherence, animations, and a new chapter on evidence-based game design. The chapter on the Cognitive Theory of Multimedia Learning introduces three forms of cognitive load which are revisited throughout each chapter as the psychological basis for chapter principles. A new chapter on engagement in learning lays the groundwork for in-depth reviews of how to leverage worked examples, practice, online collaboration, and learner control to optimize learning. The updated instructor's materials include a syllabus, assignments, storyboard projects, and test items that you can adapt to your own course schedule and students.Co-authored by the most productive instructional research scientist in the world, Dr. Richard E. Mayer, this book distills copious e-learning research into a practical manual for improving learning through optimal design and delivery.Get up to date on the latest e-learning researchAdopt best practices for communicating information effectivelyUse evidence-based techniques to engage your learnersReplace popular instructional ideas, such as learning styles with evidence-based guidelinesApply evidence-based design techniques to optimize learning gamese-Learning continues to grow as an alternative or adjunct to the classroom, and correspondingly, has become a focus among researchers in learning-related fields. New findings from research laboratories can inform the design and development of e-learning. However, much of this research published in technical journals is inaccessible to those who actually design e-learning material. By collecting the latest evidence into a single volume and translating the theoretical into the practical, e-Learning and the Science of Instructionhas become an essential resource for consumers and designers of multimedia learning.

BackgroundTeachers can have a significant impact on student interest and learning in science, technology, engineering, and math (STEM) subjects and careers. Teacher self-efficacy can also significantly affect student learning. Researchers investigated the effects of teacher professional development and integrated STEM curriculum development on teacher self-efficacy. Participants in the study included high school science and engineering technology teachers enrolled in a National Science Foundation–ITEST project called Teachers and Researchers Advancing Integrated Lessons in STEM (TRAILS). The TRAILS program sought to prepare teachers to integrate STEM content using engineering design, biomimicry, science inquiry, and 3D printing as pedagogical approaches. Teachers learned within a community of practice working alongside industry partners and college faculty. The purpose of the study was to investigate the impact of the 70 h of professional development to train three cohorts of teachers over 3 years on teacher self-efficacy. The research design utilized a quasi-experimental nonequivalent control group approach, including an experimental group and an untreated control group.ResultsMeasurements on beliefs about teacher self-efficacy were collected on pretest, posttest, and delayed posttest survey assessments. Researchers analyzed the T-STEM survey results for teaching self-efficacy using the Wilcoxson signed-rank test for detecting significant differences. Science teachers showed a significant increase in teacher self-efficacy comparing the pretest and delayed posttest scores after TRAILS professional development and STEM lesson implementation (p = .001, effect size = .95). Additionally, significant differences between groups (science experimental vs science control group teachers) using the Wilcoxon rank-sum test were detected from pretest to posttest (p = .033, effect size = .46), posttest to delayed posttest (p = .029, effect size = .47), and pretest to delayed posttest (p = .005, effect size = .64). There were no significant differences detected in the control group. Engineering technology teachers showed no significant differences between the pretest, posttest, and delayed posttest self-efficacy scores.ConclusionsThe results indicate the science teachers’ self-efficacy increased after professional development and after lesson implementation. Potential implications from this research suggest that the science teacher participants benefited greatly from learning within a community of practice, engaging in science practices, and using science knowledge to solve a real-world problem (engineering design).

This article reports the findings of a case study that investigated the perceptions of international students regarding the impact of cultural differences on their learning experiences in an online MBA program. The study also revealed that online instructors need to design courses in such a way as to remove potential cultural barriers, including language, communication tool use, plagiarism, time zone differences and a lack of multicultural content, which may affect international students' learning performances. The study indicates that a culturally inclusive learning environment needs to consider diversity in course design in order to ensure full participation by international students.

The rapid growth in the field of human–computer interaction (HCI) for individuals with visual impairment has been recognized in recent years. However, comprehensive quantitative depictions of the development of this fast-moving field have been scarce. A total of 479 documents were selected from the Web of Science Core Collection (WoSCC) database from 1999 to 2022. A large-scale scientometric analysis was implemented to objectively track emerging trends, visualize the status quo, and understand the intellectual structure along with development of the field. The results indicated a continuing growth trend in the quantity of papers on this topic. The USA is the leading country in the field, followed by the UK and India. The study has identified seven principal avenues of research: (1) usability, (2) mobile applications, (3) embodied skills, (4) assistive technology, (5) education, (6) user-centered, and (7) information technology. Future investigations are crucial for creating more inclusive, accessible, and desirable digital products for users with visual impairments, as well as for addressing their higher-order needs and experiences. In addition, further analysis and recommendations are provided in the areas of navigation systems for users with visual impairment, the development of emerging technologies such as VR and wearable products, and access to education through digital technology for people with visual impairments. In essence, this paper provides a comprehensive and systematic evaluation of research findings on HCI for visually impaired individuals, aiding researchers in staying abreast of the latest developments and identifying future research directions.

Contemporary industry practices must be appropriately reflected in designing modern-day teaching and learning programmes. Existing studies are limited to systematic methodologies for accumulating contemporary practice requirements and using that data to inform the design of educational programmes, even though various, local approaches for doing so often exist in higher education institutions. Going beyond this and adopting design-based research (DBR) principles, this paper introduces industry practitioner perspectives of contemporary- practice need for conceptualisation and design of a new business master’s degree programme. Outlining industry-demand as a driving force in stimulating a new business data-analytics programme at a medium-sized Australian metropolitan university, the study utilises open-ended interviews with five senior data analytics professionals to find a new matrix of industry expectations. The emerged elements are open-sourced tools based general technical knowledge; specific industry certifications or special skills; technology integration knowledge; cross-industry knowledge such as marketing; project management/agility and decision-making utilising appropriate supporting knowledge. Based on these findings, key learning objectives, an initial structure of the programme and specialisation subjects is proposed for further evaluation through convergent interviewing. We anticipated that the entire design process could be reusable for other similar situations for designing new practical courses in higher education sector.

This study examines how business school students with no programming background develop technical literacy through a newly introduced Digital Innovation course. Addressing a gap in non-STEM education research—where little is known about how social science students experience technical literacy interventions—we draw on qualitative data from group exam reflections (n = 14) and mid-semester survey responses (n = 7). Using an inductive thematic analysis, the study investigates how students perceived, navigated, and made sense of foundational coding activities. Four themes emerged: (1) Perceived value of coding and technical literacy, (2) Hidden gaps in foundational technical literacy, (3) AI as a cognitive and pedagogical scaffold and (4) Emerging technical competence and identity formation. Framed within theories of digital literacy and constructivist learning, the findings show how limited, scaffolded exposure to web development can shift students from digital consumption toward novice digital production. The study contributes empirical insight into how coding can be meaningfully embedded within business school curricula and offers pedagogical recommendations for designing accessible technical literacy interventions.

AI-driven technologies are reshaping the higher education landscape, particularly in assessment design and setting, execution, grading, evaluation, and feedback, in the field of management education at universities. However, a comprehensive analysis of the extent to which assessment models have evolved and the driving forces behind these shifts remains unexplored. This study aims to explore the impacts and driving factors of AI-driven technologies, including generative AI tools, automated grading and feedback systems, plagiarism detection tools, and adaptive learning platforms, on the evolution of assessment models in management education, with a particular emphasis on Sri Lanka as the chosen research context. The data collected through 15 interviews and various documents, where the number of interviews was determined based on the attainment of data saturation, were analysed using the Substitution, Augmentation, Modification, and Redefinition (SAMR) model and the three isomorphic forces in new institutional sociology. When assessing the impact of AI integration into assessment tasks, this study finds that academics reflect the modification level and augmentation level of incorporation of AI in the design and setting of assessments. Further, it suggests that academics only exhibit the substitution level for both grading and evaluation, as well as the provision of feedback within assessments. Normative pressure emerges as the primary driving force behind these integrations of AI into assessment tasks, specifically in areas such as assessment design, setting, and the provision of feedback. Additionally, the study reveals promising prospects that could be harnessed by incorporating AI tools, especially in developing countries with comparable economic, technological, social, and cultural trajectories in AI adoption within education.

The past half-century has witnessed a dramatic increase in the scale and complexity of scientific research. The growing scale of science has been accompanied by a shift toward collaborative research, referred to as \"team science.\" Scientific research is increasingly conducted by small teams and larger groups rather than individual investigators, but the challenges of collaboration can slow these teams' progress in achieving their scientific goals. How does a team-based approach work, and how can universities and research institutions support teams? Enhancing the Effectiveness of Team Science synthesizes and integrates the available research to provide guidance on assembling the science team; leadership, education and professional development for science teams and groups. It also examines institutional and organizational structures and policies to support science teams and identifies areas where further research is needed to help science teams and groups achieve their scientific and translational goals. This report offers major public policy recommendations for science research agencies and policymakers, as well as recommendations for individual scientists, disciplinary associations, and research universities. Enhancing the Effectiveness of Team Science will be of interest to university research administrators, team science leaders, science faculty, and graduate and postdoctoral students.

Background Good communication skills among community health workers (CHWs) can improve public vaccination decision-making and alleviate vaccine hesitancy. However, in China, standardized training to improve the vaccine communication skills of CHWs is insufficient and underemphasized. Accordingly, this study examined the training preferences for CHWs’ vaccine communication skills to meet the current needs of community-based vaccination services in China. Methods This study employed a discrete choice experiment (DCE) design conducted at five community health service centers in Harbin, China, between April and June 2021. Data collection included in-depth interviews and face-to-face administration of questionnaires. CHWs were recruited via convenience sampling, with eligibility criteria requiring participants to: hold vaccination qualification certificates; be full-time frontline staff with ≥ 1 year of vaccination experience; have no prior formal training in vaccine communication. A total of 164 valid questionnaires were included for analysis. Preferences for training programs were evaluated using a mixed logit model. The DCE attributes comprised training period (1 day, 3 days, 7 days), main content (vaccine basics, addressing common misconceptions, communication skills), delivery methods (online lectures, on-site seminars, case simulations), training scale (< 50, 50–100, > 100 participants), and feedback mechanisms (none, final feedback, stage-based feedback). Results Three attributes—training period, main content of the training, and training scale—significantly influenced CHWs’ training choices. CHWs preferred programs with shorter training cycles and fewer than 50 participants to improve their ability to share basic vaccine-related knowledge and had less desire to receive communication skills training. At the same time, we found no association of training modality on CHW preferences. Conclusions Using a DCE, this study investigated the preferences of CHWs for participating in a vaccine communication training program. CHWs preferred a one-day training cycle, training content focusing on vaccine basics, and a small number of people to be trained. The results of this study can inform policymakers and administrators when in China developing vaccine communication training programs for CHWs.