Over the past 15 years, a limited but growing number of studies have addressed the issue of digital ethics (DigEth) within the context of social studies online learning (SSOL), although the body of research remains limited. This study employed bibliometric methods to systematically research the field of publication on DigEth in SSOL from 2009 to 2025; 53 documents on publication were identified from the Scopus database as of March 6, 2025. The findings indicate a significant increase in publications over the past two years, although their distribution remains uneven both geographically and thematically. Accordingly, future studies are encouraged to broaden the scope of inquiry. Integrating additional databases, such as the Web of Science, could further enhance the generalizability of the findings. This study has important implications for scholars, educators, and policymakers concerned with ethical issues in digital spaces and online learning environments. Moreover, the results may open new avenues for future research and advance scholarly publications on this topic.
Understanding Artificial Intelligence's educational consequences is vital for successful instructional tactics and student engagement as technology advances. By thoroughly examining AI's effects on information accuracy, personal innovation, and pedagogical fit, the study seeks to close the gap between technology developments and educational practices. Additionally, to investigate how AI affects academic achievement and student engagement. The study, which uses a quantitative methodology and analyses data using SPSS & AMOS, covers 751 students utilizing AI-powered learning aids in various academic settings. A nuanced investigation of AI dimensions is made possible by analytical viewpoints and organized questionnaires. Major findings show that personal innovation, information accuracy, and pedagogical fit affect AI. Furthermore, AI has no discernible impact on students' performance. This analysis suggests that AI intelligence technology enhances educational standards by equipping students with essential skills to navigate future challenges.
Being absent from school can negatively impact the wellbeing of students. Telepresence robots can help absentees join their classes remotely and maintain their social connections. Nonetheless, remote students might still feel like bystanders during group activities. We investigate whether using a moderator can improve the inclusion of remote students. In a between-subject experiment, 84 participants (56 on-site, 28 remote) completed a language learning task in small hybrid groups. In the experimental condition, a robot moderator facilitated the group work, while in the baseline condition participants completed their task without a moderator. Analysis of video data shows that participants in experimental condition experienced significantly closer physical proximity and more frequent eye-level communication. The findings suggest that moderation positively influenced group dynamics and benefited remote students.
Online teaching has become a pathway to serve students across markets and to enable instruction across time and distance. This study examines the students' perspectives on what teaching methods enable student engagement in the institution and what methods encourage students to take advantage of the technological interface to cheat. Data show that class structure, faculty communication, and collaborative processes increase student engagement. Using techniques such as breakout groups, games, and less personal communication increases the likelihood that students will cheat in the online environment. The study supports keeping the human factor in the online classroom as an essential element of student engagement.
In higher education institutions, as the number of online language courses continues to grow, it is essential to equip faculty with the support and tools necessary to enhance learning experiences for students with visual impairments. Grounded in Culturally Relevant Disability Pedagogy and Disability Studies Theory, this study advocates for more equitable and accessible course design for underrepresented learners. Using a qualitative Interpretative Phenomenological Analysis (IPA) approach, the study examines online language faculty's lived experiences teaching students with visual impairments. A purposive sample of 10 language faculty members across the United States participated in in-depth, semi-structured interviews conducted via videoconferencing. Interviews were audio-recorded, transcribed verbatim, and analyzed iteratively through close reading, initial coding, and the development of emergent and superordinate themes. The study was guided by the following research questions: 1) What are faculty experiences in delivering online language courses to students with visual impairments? 2) How do faculty describe the support and training they receive in delivering accessible online language courses? 3) What are the strategies and tools faculty use when teaching languages to students with visual impairments online? Findings indicate that Americans with Disabilities Act (ADA) compliance in online language instruction requires greater prioritization. Participants described limited institutional support and insufficient training in accessible course design, often relying on self-directed learning and reactive adaptations. These findings underscore the need for more systematic and proactive approaches to accessibility in online language education to ensure that visually impaired learners can fully engage and succeed academically.
Hybrid (online/in-person) learning has revealed mixed student satisfaction and adding high-content courses like human anatomy into hybrid formats can pose significant learning challenges due to their extensive material. This study explores the integration of artificial intelligence (AI) tools in a hybrid human anatomy course to enhance student learning and performance. For a non-randomized study involving 129 hybrid Doctor of Physical Therapy students, our multidisciplinary team developed supplemental AI-driven tools. The tools included a virtual dashboard, an assessment feedback application, and a custom chatbot, aimed at facilitating early remediation and improving hybrid student outcomes. Final course grades were not significantly different between cohorts who had access and no access to the AI tools. However, among the AI tool users, over 80% of participants reported the AI tools as helpful. Additionally, within the AI tool user cohort, participants who may have consistently used the AI tools achieved higher academic performances than inconsistent AI tool users. Discussion: These findings suggest that supplemental AI tools when used consistently may assist in improving hybrid students' understanding and mastery of complex subjects. This research provides a foundation for developing intelligent feedback mechanisms to support hybrid student learning.
Este estudio investiga las pr & aacute;cticas de facilitaci & oacute;n empleadas en un Programa de Desarrollo Profesional (PDP) online en una escuela vulnerable en Chile, enfatizando su impacto en la participaci & oacute;n docente y la pedagog & iacute;a durante una transici & oacute;n significativa debido a la pandemia de COVID-19. La literatura existente subraya el papel esencial de los PDP eficaces para mejorar las habilidades de los docentes y, posteriormente, mejorar los resultados de los estudiantes; sin embargo, muchos programas no logran los resultados deseados. A trav & eacute;s de un estudio de caso cualitativo que involucr & oacute; a 20 participantes, incluidos 13 docentes de aula y 7 facilitadores, la investigaci & oacute;n identifica tres pr & aacute;cticas de facilitaci & oacute;n clave: interacci & oacute;n, contenido y pedagog & iacute;a. Estas pr & aacute;cticas resaltan la articulaci & oacute;n din & aacute;mica entre facilitadores y docentes, enfatizando la construcci & oacute;n de relaciones, la relevancia del contenido y las estrategias pedag & oacute;gicas adaptativas para abordar los desaf & iacute;os contextuales. Los hallazgos revelan que la capacidad de los facilitadores para fomentar la confianza, brindar retroalimentaci & oacute;n espec & iacute;fica y adaptar el contenido para alinearlo con las prioridades del plan de estudios contribuy & oacute; significativamente al crecimiento profesional de los docentes y a la participaci & oacute;n de los estudiantes en actividades de resoluci & oacute;n de problemas. Adem & aacute;s, la transici & oacute;n a un formato online requiri & oacute; enfoques innovadores para mantener la colaboraci & oacute;n y entornos de aprendizaje efectivos. En & uacute;ltima instancia, esta investigaci & oacute;n subraya la necesidad cr & iacute;tica de una preparaci & oacute;n eficaz de los facilitadores y el desarrollo de estrategias flexibles en el dise & ntilde;o del PDP para garantizar una mejora sostenible en las pr & aacute;cticas educativas, llamando la atenci & oacute;n sobre la intrincada relaci & oacute;n entre los facilitadores, los docentes y los contextos en los que operan.
The paper develops pricing formulas for new offerings which ensure that a minimum "hurdle" of return is met. The first formula is based on profit per enrollee, and the second one on return on investment (ROI). Either one can depend on elasticity of demand through a scale, with higher hurdle rates for lower elasticities. Increasing the hurdle rates sufficiently can cover overhead or indirect costs. The analysis examines the decision to proceed or cancel an offering if actual enrollment is low. This is shown to depend on whether sunk costs have been incurred. To enhance profit through hurdle rates, a self-supported unit should choose offerings with a low cost per enrollee, which are differentiated from other offerings in the market so that demand is as inelastic as possible, and with a high expected demand. Related simulations indicate that a unit can increase the hurdle rate exponentially as product differentiation increases. By contrast, losses materialize quickly with offerings that are not differentiated enough. The analysis concludes by characterizing several instructor compensation rules that are incentivizing instructors.
This study investigates AI use for assignment completion in distance education by focusing on two cognitive predictors, cognitive load and cognitive distortion, and by testing perceived study stress as a moderator of these relationships. We used Structural Equation Modeling-Partial Least Squares (SEM-PLS) to analyze survey data from undergraduate to doctoral students. In total, 308 students from multiple Indonesian provinces completed the questionnaire via Google Forms. The results indicate positive associations between cognitive load, cognitive distortion, and AI-usage intensity, whereas perceived study stress does not strengthen those effects in the moderation tests reported. The study contributes by linking cognitive conditions and technology-use behavior in a single model and by specifying how stress appraisal was expected to shape reliance on AI in distance-learning tasks. The final section provides recommendations derived from the observed patterns in the data.
By its nature, online learning is a learner-centered process and, therefore, self-regulation (i.e. the ability to manage one's own learning) plays a significant role. In this study, we aimed to adapt and validate the Online Learning Readiness Self-Check Survey (OLRSC), a 39-item instrument that measures self-regulated learning readiness across domains such as learning, resources, technology, and interaction management. To this end, we administered the full translated scale to undergraduate students (n = 706) at a public university in T & uuml;rkiye during the Spring 2022. Using exploratory and confirmatory factor analyses on split samples, we identified a three-factor structure comprising 25 items: learning management, interaction management, and interaction with peers. The resulting scale demonstrated acceptable fit indices and strong internal consistency (Cronbach's alpha = .81-.91), indicating that the Turkish adaptation of the OLRSC is a valid and reliable tool for assessing online learning readiness among Turkish undergraduate students.
El estr & eacute;s, la ansiedad y la depresi & oacute;n se asocian con la salud mental del estudiantado universitario, y la educaci & oacute;n en l & iacute;nea constituye un contexto en el que estas condiciones han sido ampliamente estudiadas. El objetivo de este estudio fue analizar la relaci & oacute;n entre estos problemas de salud mental y diversos h & aacute;bitos de vida, estrategias de afrontamiento, compromiso acad & eacute;mico y procrastinaci & oacute;n en estudiantado universitario que cursa programas en l & iacute;nea. Se realiz & oacute; un estudio transversal con una muestra de 2204 estudiantes universitarios con una edad media de 34.66 +/- 9.15 a & ntilde;os, procedentes de una universidad con metodolog & iacute;a en l & iacute;nea, quienes completaron cuestionarios validados para evaluar los niveles de estr & eacute;s, ansiedad y depresi & oacute;n, as & iacute; como la calidad del sue & ntilde;o, la actividad f & iacute;sica, la adherencia a la dieta mediterr & aacute;nea, el tiempo de pantalla, las estrategias de afrontamiento, el compromiso acad & eacute;mico y el burnout. Los resultados mostraron prevalencias del 31.62% para el estr & eacute;s, del 32.30% para la ansiedad y del 27.22% para la depresi & oacute;n. Asimismo, se identificaron asociaciones entre una peor calidad del sue & ntilde;o, menores niveles de actividad f & iacute;sica, mayor tiempo de exposici & oacute;n a pantallas y una menor adherencia a la dieta mediterr & aacute;nea y mayores niveles de estr & eacute;s, ansiedad y depresi & oacute;n. El estudiantado con sintomatolog & iacute;a severa present & oacute; menores niveles de compromiso acad & eacute;mico, un menor uso de estrategias de afrontamiento adaptativas y mayores niveles de procrastinaci & oacute;n. En conjunto, estos resultados aportan evidencia sobre la relaci & oacute;n entre h & aacute;bitos de vida, variables acad & eacute;micas y salud mental en el contexto de la educaci & oacute;n universitaria en l & iacute;nea.
Se describen dos cursos te & oacute;rico-pr & aacute;cticos e intensivos de pregrado, con el modelo biol & oacute;gico Drosophila melanogaster, impartidos mediante la ense & ntilde;anza remota de emergencia durante la pandemia de COVID-19 y despu & eacute;s de & eacute;sta, en la Universidad Nacional Aut & oacute;noma de M & eacute;xico (UNAM). Utilizando una combinaci & oacute;n de dise & ntilde;o in silico para realizar CRISPR/Cas9 con herramientas de acceso libre en l & iacute;nea y la realizaci & oacute;n de sencillos experimentos quimiosensoriales en casa. Los cursos tuvieron como objetivo mantener la continuidad educativa durante la pandemia COVID-19 y fortalecer habilidades de investigaci & oacute;n esenciales en la formaci & oacute;n cient & iacute;fica de pregrado. La metodolog & iacute;a involucr & oacute; tareas estructuradas para realizar en casa, sesiones individuales a distancia y seminarios grupales virtuales sincr & oacute;nicos semanales, durante 16 semanas cada curso, con el prop & oacute;sito de fomentar habilidades alineadas con el perfil del programa de pregrado en Biolog & iacute;a de la UNAM. Los resultados demostraron un alto compromiso estudiantil y la finalizaci & oacute;n exitosa de los objetivos de aprendizaje, incluyendo la producci & oacute;n de videos instructivos y reportes de la investigaci & oacute;n en l & iacute;nea y pr & aacute;ctica. El proyecto destac & oacute; la viabilidad y efectividad de la formaci & oacute;n cient & iacute;fica a distancia, proporcionando un marco de aprendizaje sostenible que sigui & oacute; despu & eacute;s de la pandemia COVID-19, y considera posibles futuras interrupciones de las actividades universitarias y/o para estudiantes con acceso limitado a la infraestructura educativa presencial.
K-12 virtual programs may apply quality assurance metrics, including Quality Matters (TM) (QM) external peer reviews. Virtual teachers, or teachers who use web-based tools to instruct without geographic or time constraints, may support program initiatives and serve as Course Representatives for QM peer reviews. Professional capacity is a concern with this practice, as virtual teachers' responsibilities emphasize daily instruction, not QM's primary focus: course design. However, the experience of serving as a Course Representative may provide an enduring professional opportunity. This qualitative case study applied document analysis and semi-structured interviews to explore the experiences and perspectives of seven virtual teachers who served as Course Representatives for organizationally designed course peer reviews. Data was analyzed using deductive codes from Ali and Wright's (2017) Online Faculty Professional Development model and inductive codes focused on participants' experiences. Participants revealed a challenging, yet achievable work scope made possible with program support. They also perceived a professional development experience that could enhance instructional and leadership rolls. Implications include designing QM-based roles as intentional professional development and considerations for programs and teachers engaged in quality assurance initiatives.
This study develops and validates a multidimensional benchmarking instrument to evaluate the pedagogical quality of sNOOCs (social massive open online courses), integrating dimensions related to pedagogical design, usability, artificial intelligence (AI) and the metaverse. Through an instrumental validation study with a sequential-explanatory mixed methodology design. Using a sequential explanatory mixed-methods approach, a 24-item questionnaire was designed and administered in a peer assessment conducted by 135 postgraduate students at UNED (Spanish University of Distance Education), generating 937 assessments. The psychometric results confirm the excellent reliability of the instrument (Cronbach's alpha = 0.97) and its structural validity, with a factor analysis explaining 77.6% of the variance. The findings reveal that pedagogical design is the highest-rated dimension, followed by usability and the quality of AI, showing a strong correlation among them. By contrast, the integration of the metaverse emerges as the main challenge, receiving the lowest rating and showing the greatest dispersion, indicating a lack of effective pedagogical alignment. The research validates peer assessment as a robust methodological strategy and offers a practical tool for continuous improvement of instructional design in advanced digital educational settings, while underlining the need for intentional pedagogical integration of emerging technologies.
Generative Artificial Intelligence (GenAI) holds significant potential to transform the educational landscape, offering new opportunities and challenges for teaching and learning. The release of advanced tools like ChatGPT has accelerated interest in exploring their applications and implications. Despite its growing use, it is necessary to understand how instructors utilize GenAI, how different instructor demographic groups perceive their readiness to use GenAI, and the benefits and challenges of its use in teaching and learning. This survey study was conducted in the spring of 2024 and involved 139 university instructors in U.S. public universities. Data was analyzed using descriptive analysis, ANOVA, and correlation. The findings indicate that while university instructors frequently use GenAI for general purposes, they are less comfortable and less likely to use it for teaching. Many instructors feel reasonably comfortable designing learning activities with these tools. Perceptions of GenAI varied significantly by instructors' rank and discipline, with adjuncts and social sciences faculty perceiving fewer benefits and greater challenges. Additionally, instructors who taught more courses found GenAI tools less challenging, whereas older instructors perceived more limitations. These findings suggest that policies, guidelines, and professional development should consider instructor differences to address the varying adoption rates and perceptions of ethical use.
This study explores how online educators in Indian higher education interpret and experience the integration of ChatGPT in their teaching practice. Using Interpretative Phenomenological Analysis, in-depth interviews were conducted with 38 educators from diverse higher education institutions to examine both enabling and constraining aspects of ChatGPT use. Participants described the tool as supporting instructional efficiency, particularly in relation to teaching preparation and student engagement. Moreover, educators expressed concerns regarding data privacy, content reliability, academic integrity, and the risk of excessive student dependence on AI-generated outputs. Uncertainty surrounding institutional policies and assessment guidelines leads to cautious and selective adoption. From an interpretive perspective, the findings suggest that educators view ChatGPT not simply as a technical resource but as a tool that requires ongoing professional judgment and ethical consideration. By foregrounding educators' lived experiences, this study addresses an important gap in the literature, particularly within the Indian online higher education context, where qualitative evidence on faculty engagement with generative AI remains limited.
