A multimethod synthesis of Covid-19 education research: the tightrope between covidization and meaningfulness.

This study offers a comprehensive analysis of COVID-19 research in education. A multi-methods approach was used to capture the full breadth of educational research. As such, a bibliometric analysis, structural topic modeling, and qualitative synthesis of top papers were combined.

Affective states and regulation of learning during socio-emotional interactions in secondary school collaborative groups.

Background: Group affective states for learning are constantly formed through socio-emotional interactions. However, it remains unclear how the affective states vary during collaboration and how they occur with regulation of learning. Appropriate methods are needed to track both group affective states and these interaction processes.

A Quantitative Synthesis of Eight Decades of Global Multiple Sclerosis Research Using Bibliometrics.

Bibliometric studies on the field of multiple sclerosis (MS) research are scarce. The aim of this study is to offer an overarching view of the body of knowledge about MS research over eight decades-from 1945 to 2021-by means of a bibliometric analysis. We performed a quantitative analysis of a massive dataset based on Web of Science.

Utility of SPECT Functional Neuroimaging of Pain.

Functional neuroimaging modalities vary in spatial and temporal resolution. One major limitation of most functional neuroimaging modalities is that only neural activation taking place inside the scanner can be imaged. This limitation makes functional neuroimaging in many clinical scenarios extremely difficult or impossible.

Tear down the walls: Disseminating open access research for a global impact.

Objective: Publications are the cornerstone of the dissemination of scientific innovation and scholarly work, but published works are mostly behind paywalls. Therefore, many researchers and institutions are searching for alternative models for disseminating scholarly work that bypasses the current structure of paywalls. This study aimed to determine whether a self-published open access (OA) journal, the International Journal of Health Sciences (IJHS), has been able to reach a global audience in terms of authorship, readership, and impact using the OA model.

Robustness and rich clubs in collaborative learning groups: a learning analytics study using network science.

Productive and effective collaborative learning is rarely a spontaneous phenomenon but rather the result of meeting a set of conditions, orchestrating and scaffolding productive interactions. Several studies have demonstrated that conflicts can have detrimental effects on student collaboration. Through the application of network science, and social network analysis in particular, this learning analytics study investigates the concept of group robustness; that is, the capacity of collaborative groups to remain functional despite the withdrawal or absence of group members, and its relation to group performance in the frame of collaborative learning.

What makes an online problem-based group successful? A learning analytics study using social network analysis.

Background: Although there is a wealth of research focusing on PBL, most studies employ self-reports, surveys, and interviews as data collection methods and have an exclusive focus on students. There is little research that has studied interactivity in online PBL settings through the lens of Social Network Analysis (SNA) to explore both student and teacher factors that could help monitor and possibly proactively support PBL groups. This study adopts SNA to investigate how groups, tutors and individual student's interactivity variables correlate with group performance and whether the interactivity variables could be used to predict group performance.

The role of social network analysis as a learning analytics tool in online problem based learning.

Background: Social network analysis (SNA) might have an unexplored value in the study of interactions in technology-enhanced learning at large and in online (Problem Based Learning) PBL in particular. Using SNA to study students' positions in information exchange networks, communicational activities, and interactions, we can broaden our understanding of the process of PBL, evaluate the significance of each participant role and learn how interactions can affect academic performance. The aim of this study was to study how SNA visual and mathematical analysis can be sued to investigate online PBL, furthermore, to see if students' position and interaction parameters are associated with better performance.

Research education in an undergraduate curriculum: Students perspective.

Objective: This study aims to investigate the attitude and practice toward undergraduate research studies among medical students at Qassim University in Buraydah, Saudi Arabia.

Methods: An online cross-sectional survey developed based on previous studies. It was announced to all registered medical students who have active college's email ( = 448) at Qassim University in Buraydah, Saudi Arabia during the academic year of 2016.

Using social network analysis to understand online Problem-Based Learning and predict performance.

Social network analysis (SNA) may be of significant value in studying online collaborative learning. SNA can enhance our understanding of the collaborative process, predict the under-achievers by means of learning analytics, and uncover the role dynamics of learners and teachers alike. As such, it constitutes an obvious opportunity to improve learning, inform teachers and stakeholders.

A literature review of empirical research on learning analytics in medical education.

The number of publications in the field of medical education is still markedly low, despite recognition of the value of the discipline in the medical education literature, and exponential growth of publications in other fields. This necessitates raising awareness of the research methods and potential benefits of learning analytics (LA). The aim of this paper was to offer a methodological systemic review of empirical LA research in the field of medical education and a general overview of the common methods used in the field in general.

How social network analysis can be used to monitor online collaborative learning and guide an informed intervention.

To ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students' interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved.

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

Background: Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance.

How learning analytics can early predict under-achieving students in a blended medical education course.

Aim: Learning analytics (LA) is an emerging discipline that aims at analyzing students' online data in order to improve the learning process and optimize learning environments. It has yet un-explored potential in the field of medical education, which can be particularly helpful in the early prediction and identification of under-achieving students. The aim of this study was to identify quantitative markers collected from students' online activities that may correlate with students' final performance and to investigate the possibility of predicting the potential risk of a student failing or dropping out of a course.

Shall Migraine be Considered a Simple Benign Headache Disorder?

Migraine is a primary headache disorder which has received little attention from health care policies and physicians. This has led to ineffective management and more suffering to the patients and society. Migraine per se is a disabling disease which has its impact on the patient, family and work.