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The COVID-19 pandemic has had a significant impact on students' academic performance. The effects of the pandemic have varied among students, but some general trends have emerged. One of the primary challenges for students during the pandemic has been the disruption of their study habits. Students getting used to online learning routines might find it even more challenging to perform well in face to face learning. Therefore, assessing various potential risk factors associated with students low performance and its prediction is important for early intervention. As students' performance data encompass diverse behaviors, standard machine learning methods find it hard to get useful insights for beneficial practical decision making and early interventions. Therefore, this research explores regularized ensemble learning methods for effectively analyzing students' performance data and reaching valid conclusions. To this end, three pruning strategies are implemented for the random forest method. These methods are based on out-of-bag sampling, sub-sampling and sub-bagging. The pruning strategies discard trees that are adversely affected by the unusual patterns in the students data forming forests of accurate and diverse trees. The methods are illustrated on an example data collected from university students currently studying on campus in a face-to-face modality, who studied during the COVID-19 pandemic through online learning. The suggested methods outperform all the other methods considered in this paper for predicting students at the risk of academic failure. Moreover, various factors such as class attendance, students interaction, internet connectivity, pre-requisite course(s) during the restrictions, etc., are identified as the most significant features.

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Objective: The variability and opportunistic nature of surgical clinical education is the main problem for effective teaching and training of medical students. Incorporating online mediums including discussion forums, interactive videos/scenarios, static pages, and quizzes is known as blended learning (BL). This study aimed to compare the intrinsic motivation of surgical students enrolled in blended learning to those enrolled in face-to-face teaching (f2f teaching). Methods: A quasi-experimental, cross-over study was conducted in Surgical Unit-I and Surgical Unit-II of Dow University Hospital, Karachi, from March to August 2014. A total of 31 students participated and were exposed to two different teachings. For the first four weeks, Group A was posted in Surgical-I (f2f teaching) and Group B in Surgical-II (BL). Both groups were taught the same contents with the same schedule. The F2F group had clinical exposure to real patients, and small group discussions (SGDs) while The BL group students were exposed to an additional online learning component. Intrinsic Motivation Inventory (IMI) was administered at the end of four weeks and groups were swapped. Exchanged groups were again taught the same contents with the same schedule for another four weeks and IMI was administered. Results: Fifty-eight students completed IMI; 28 in f2f and 30 in BL group. There was a significant difference in all four subscales of IMI between the two groups. In three subscales, students in BL were more motivated as compared to f2f (p<0.01). Students in f2f experienced more perceived tension than in BL (p<0.048). Conclusion: This study concluded that blended surgical learning programs keep medical students more intrinsically motivated to learn. By utilizing online learning, superior educational opportunities for students can be cultivated. It can result in enhanced faculty effectiveness and efficiency as well.

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Viewing multiple images of a newly encountered face improves recognition of that identity in new instances. Studies examining face learning have presented high-variability (HV) images that incorporate changes that occur from moment-to-moment (e.g., head orientation and expression) and over time (e.g., lighting, hairstyle, and health). We examined whether low-variability (LV) images (i.e., images that incorporate only moment-to-moment changes) also promote generalisation of learning such that novel instances are recognised. Participants viewed a single image, six LV images, or six HV images of a target identity before being asked to recognise novel images of that identity in a face matching task (training stimuli remained visible) or a memory task (training stimuli were removed). In Experiment 1 (n = 71), participants indicated which image(s) in 8-image arrays belonged to the target identity. In Experiment 2 (n = 73), participants indicated whether sequentially presented images belonged to the target identity. Relative to the single-image condition, sensitivity to identity improved and response biases were less conservative in the HV condition; we found no evidence of generalisation of learning in the LV condition regardless of testing protocol. Our findings suggest that day-to-day variability in appearance plays an essential role in acquiring expertise with a novel face.

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Previous experiments have shown that a brief encounter with a previously unfamiliar person leads to the establishment of new facial representations, which can be activated by completely novel pictures of the newly learnt face. The present study examined how stable such novel neural representations are over time, and, specifically, how they become consolidated within the first 24 h after learning. Using event-related brain potentials (ERPs) in a between-participants design, we demonstrate that clear face familiarity effects in the occipito-temporal N250 are evident immediately after learning. These effects then undergo change, with a nearly complete absence of familiarity-related ERP differences 4 h after the initial encounter. Critically, 24 h after learning, the original familiarity effect re-emerges. These findings suggest that the neural correlates of novel face representations are not stable over time but change during the first day after learning. The resulting pattern of change is consistent with a process of consolidation.

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Ensemble coding - the rapid extraction of a perceptual average - has been proposed as a potential mechanism underlying face learning. We tested this proposal across five pre-registered experiments in which four ambient images of an identity were presented in the study phase. In Experiments 1 and 2a-c, participants were asked whether a test image was in the study array; these experiments examined the robustness of ensemble coding. Experiment 1 replicated ensemble coding in an online sample; participants recognize images from the study array and the average of those images. Experiments 2a-c provide evidence that ensemble coding meets several criteria of a possible learning mechanism: It is robust to changes in head orientation (± 60o), survives a short (30s) delay, and persists when images of two identities are interleaved during the study phase. Experiment 3 examined whether ensemble coding is sufficient for face learning (i.e., facilitates recognition of novel images of a target identity). Each study array comprised four ambient images (variability + average), a single image, or an average of four images (average only). Participants were asked whether a novel test image showed the identity from a study array. Performance was best in the four-image condition, with no difference between the single-image and average-only conditions. We conclude that ensemble coding of facial identity is robust but that the perceptual average per se is not sufficient for face learning.

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This study is designed to evaluate students' knowledge and perceptions about the online learning of pharmacy curricula in Iraq during the COVID-19 quarantine. A descriptive, cross-sectional study involving 278 pharmacy students was done between October 2020 and June 2021. About 42.44% preferred face-face lecturers over other modes of delivery for lectures in the pharmacy curriculum. Most participants preferred both active learning and face-face lectures. The results show that 72.66% of responders chose to stay at home as one of the privileges of e-learning. However, the main barriers that associated with e-learning were lack of patient involvement and some technical issues regarding IT equipment, (74.82%) and (62.23%), respectively. E-learning is seen as a lack of social presence, less social contact, and synchronization of connections. However, e-learning undoubtedly benefits students in several ways. Online learning is an essential podium for students to achieve their studies in periods of crisis.

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Purpose: As a result of COVID-19 pandemic, medical education at the Arabian Gulf University was instructed to apply online teaching instead of face-to-face for all phases of teaching at the University. Phase-1 is concerned with basic science courses delivered to year 1 students. We conducted this study to detect if there are any differences in the performance of medical students between online and face-to-face ways of learning. Also, a comparison between male and female performance in scientific courses was carried out in pre and during COVID-19 periods. Methods: The participant were first year students for pre COVID-19 period from 2018 to 2019 and during COVID-19 period from 2020 to 2021. The university used Moodle and Zoom as an online way of teaching. The students' performance in the year 1 (three-semester) -online period of teaching were compared with a three-semester-performance of conventional teaching prior to COVID-19. This is a retrospective study that attempts to shed some light on the efficiency of AGU experience in online learning for year 1 (Phase I) students. This study evaluates the outcome of both, online and face-to-face examinations for scientific courses. Results: The results showed that the mean performance of year one medical students in all basic scientific courses (Phase I) during the coronavirus pandemic was greater than the mean performance before the pandemic with the exception of the Biostatistics course. The results by gender showed that the mean performance of females was better than males across all scientific courses before coronavirus. Also, during the COVID pandemic, the mean performance of females was better than males in all basic science courses. Conclusion: Year -1 students' performance in science courses during the coronavirus period seems better than pre COVID19 era. Females' performance was better than males' in both periods; pre and during COVID -19 periods.

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The learning of new facial identities and the recognition of familiar faces are crucial processes for social interactions. Recently, a combined computational modeling and functional magnetic resonance imaging (fMRI) study used predictive coding as a biologically plausible framework to model face identity learning and to relate specific model parameters with brain activity (Apps and Tsakiris, Nat Commun 4, 2698, 2013). On the one hand, it was shown that behavioral responses on a two-option face recognition task could be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. On the other hand, brain activity in specific brain regions was associated with these parameters. More specifically, brain activity in the superior temporal sulcus (STS) varied with contextual familiarity, whereas activity in the fusiform face area (FFA) covaried with the prediction error parameter that updated facial familiarity. Literature combining fMRI assessments and computational modeling in humans still needs to be expanded. Furthermore, prior results are largely not replicated. The present study was, therefore, specifically set up to replicate these previous findings. Our results support the original findings in two critical aspects. First, on a group level, the behavioral responses were modeled best by the same computational model reported by the original authors. Second, we showed that estimates of these model parameters covary with brain activity in specific, face-sensitive brain regions. Our results thus provide further evidence that the functional properties of the face perception network conform to central principles of predictive coding. However, our study yielded diverging findings on specific computational model parameters reflected in brain activity. On the one hand, we did not find any evidence of a computational involvement of the STS. On the other hand, our results showed that activity in the right FFA was associated with multiple computational model parameters. Our data do not provide evidence for functional segregation between particular face-sensitive brain regions, as previously proposed.

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Background: The coronavirus disease 2019 (COVID-19) pandemic upended the educational system around the globe. During this challenging period, universities and colleges looked for other effective alternative methods of learning, such as Virtual Learning Environments (VL). Besides, Ahlia University has implemented E-learning in response to COVID-19. There needs to be more attention given to the challenges associated with technology adoption facing interior design and architecture programs, where over 60% of courses are practical, especially design studios, which form the core of the curriculum. According to a review of the relevant literature, there needs to be more research on blended learning in interior design and architecture. In order to enhance the teaching and learning of interior design and architecture, further research is required to combine cutting-edge techniques and technology. The aim of this study was to review the classroom materials for Ahlia University's interior design studio. Methods: After completing the INTD 212, INTD 216, INTD 311, and INTD 404 studios in mid-March 2022, a short Qualtrics poll was done to assess the difficulties of e-learning and offer potential consequences. Results: Though students were conveniently attending courses online, there was not much discussion and interaction like in the face-to-face model. Blended teaching in design studio courses offered many benefits. The results showed that blended design studios achieved pedagogical results as students developed their knowledge. Conclusions: Based on the findings, this research concludes that teaching and learning should be shifted from face-to-face and online learning to the best practice of a blended format.

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BACKGROUND: The acceptance of online courses by medical and dental students, especially during the coronavirus disease 2019 crisis, is substantial, as reported in various studies. However, the unfavourable online learning experiences of the students during the pandemic were also highlighted. As the teaching-learning process is returning to the "new normal," it is necessary to identify online learning domains implemented during the pandemic crisis that may be applied in pre-clinical courses in the future. METHODS: A validated Student Online Learning Readiness questionnaire assessed pre-clinical students' online learning competence. Students' academic performance in face-to-face post-pandemic was compared with their performance in online settings during the pandemic crisis. Students' satisfaction with online learning was evaluated using a self-made survey questionnaire. Descriptive statistics, the t-test, and multiple regression analysis were used to analyze the data gathered with a p-value ≤ 0.05 considered statistically significant. RESULTS: Except for social skills with classmates and groupmates, in which 47.5% of respondents indicated unreadiness, most students were prepared for online learning. Theory-wise, online learners outperformed traditional learners, but the difference was insignificant. In contrast, students' practical skills in face-to-face modality are significantly higher (p = 0.029). Students rated their satisfaction with online learning higher for interactions with instructors and staff and lower for interactions with classmates and group mates and skill acquisition. CONCLUSION: Providing high-quality pre-clinical online teaching was achieved for theoretical components but not practical skills acquisition. Students' social engagement with peers is one of the key elements crucial to online learning success. Academic leaders and curriculum developers must recognize potential gaps as they transition to online learning.

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Developmental prosopagnosia is a relatively common visuo-cognitive condition, characterised by impaired facial identity recognition. Impairment severity appears to reside on a continuum, however, it is unknown whether instances of milder deficits reflect the successful use of spontaneous (typical) face recognition strategies, or the application of extraneous compensatory cues to recognition. Here, we explore this issue in two studies. First, 23 adults with developmental prosopagnosia were asked about their use of spontaneous versus compensatory face recognition techniques in everyday life, using a series of closed- and open-ended questions. Second, the same participants performed a computerised famous face recognition task where they were asked to provide reasons why they could make any successful identifications. Findings from both studies suggest that people with developmental prosopagnosia can successfully, and quite frequently, use compensatory strategies to recognition, and that these cues support the majority of instances of preserved familiar face recognition. In contrast, 16 of the 23 participants were able to spontaneously recognise familiar faces on at least some occasions, but there were vast individual differences in frequencies of success. These findings have important implications for our conceptualisation of the condition, as well as for diagnostic practice.

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It is well-established that familiar and unfamiliar faces are processed differently, but surprisingly little is known about how familiarity builds up over time and how novel faces gradually become represented in the brain. Here, we used event-related brain potentials (ERPs) in a pre-registered, longitudinal study to examine the neural processes accompanying face and identity learning during the first eight months of knowing a person. Specifically, we examined how increasing real-life familiarity affects visual recognition (N250 Familiarity Effect) and the integration of person-related knowledge (Sustained Familiarity Effect, SFE). Sixteen first-year undergraduates were tested in three sessions, approximately one, five, and eight months after the start of the academic year, with highly variable "ambient" images of a new friend they had met at university and of an unfamiliar person. We observed clear ERP familiarity effects for the new friend after one month of familiarity. While there was an increase in the N250 effect over the course of the study, no change in the SFE was observed. These results suggest that visual face representations develop faster relative to the integration of identity-specific knowledge.

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The SARS-CoV-2 coronavirus (COVID-19) pandemic is in constant evolution, much like the virus, and we must learn to adapt our undergraduate education and learning strategies to enable students to complete their studies. This narrative review focuses on what is currently known about the face-to-face and e-learning strategies of undergraduate medical students in resource-limited settings during the COVID-19 pandemic. The majority of studies, involving health professional students, took place in 2020. Few involved educators. Students have faced challenges with the transition to remote learning, for which a couple of interventions have been devised. Bridging the gap in access and utilisation of remote learning might have required more time, however, the COVID-19 pandemic has accelerated the learning curve and the transition from in-person to online learning.

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We propose a hyperscanning research design, where electroencephalographic (EEG) data were collected on an instructor and teams of learners. We compared neurophysiological measures within the frequency domain (delta, theta, alpha, and beta EEG bands) in the two conditions: face-to-face and remote settings. Data collection was carried out using wearable EEG systems. Conversational analysis was previously applied to detect comparable EEG time blocks and semantic topics. The digitalization of training can be considered a challenge but also a chance for organizations. However, if not carefully addressed, it might constitute a criticality. Limited research explored how remote, as opposed to face-to-face, training affects cognitive, (such as memory and attention), affective, and social processes in workgroups. Data showed an alpha desynchronization and, conversely, a theta and beta synchronization for the face-to-face condition. Moreover, trainees showed different patterns for beta power depending on the setting condition, with significantly increased power spectral density (PSD) in the face-to-face condition. These results highlight the relevance of neurophysiological measures in testing the e-learning process, in relation to the emotional engagement, memory encoding, and attentional processing.

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The restriction measures put in place during the COVID-19 pandemic posed notable challenges for formal teaching-learning processes because they had to be adapted to ensure health security. An active learning programme applied to three environments (indoors, outdoors, and online) was tested with 273 undergraduate university students in a within-subjects experimental study. Each student was assigned to two indoor and two outdoor seminars, with a subsample (n = 30) also participating in online seminars implemented in response to the university's lockdown protocols. The learning experience and learning conditions were evaluated through six dimensions: learning, evaluative impact, hedonic experience, technical conditions, environmental conditions, and health security. Outdoor seminars were more effective than indoor seminars in terms of the learning experience, with greater differences in hedonic experience, while the indoor seminars were rated more highly than the outdoor seminars in terms of learning conditions, with a larger difference in the environmental conditions. No differences were found between online and face-to-face environments in terms of the learning experience, even though the online environment yielded better scores in the learning conditions. Apparently, this adaptation to both outdoor and online contexts through active methodologies allows overcoming of technical, environmental, and teaching limitations and improves health security, while ensuring a good learning experience and added flexibility to teaching-learning processes. Supplementary Information: The online version contains supplementary material available at 10.1007/s10984-023-09456-y.

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Faces learnt in a single experimental session elicit a familiarity effect in event-related brain potentials (ERPs), with more negative amplitudes for newly learnt relative to unfamiliar faces in the N250 component. However, no ERP study has examined face learning following a brief real-life encounter, and it is not clear how long it takes to learn new faces in such ecologically more valid conditions. To investigate these questions, the present study examined whether robust image-independent representations, as reflected in the N250 familiarity effect, could be established after a brief unconstrained social interaction by analysing the ERPs elicited by highly variable images of the newly learnt identity and an unfamiliar person. Significant N250 familiarity effects were observed after a 30-min (Experiment 1) and a 10-min (Experiment 2) encounter, and a trend was observed after 5 min of learning (Experiment 3), demonstrating that 5-10 min of exposure were sufficient for the initial establishment of image-independent representations. Additionally, the magnitude of the effects reported after 10 and 30 min was comparable suggesting that the first 10 min of a social encounter might be crucial, with extra 20 min from the same encounter not adding further benefit for the initial formation of robust face representations.

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Social distancing has been essential during the COVID-19 pandemic to slow the spread of the disease. Online learning ensures students can participate in learning activities while also maintaining a physical distance from other students. Although online learning was used to prevent the spread of COVID-19, the development of online learning has also been promoted. Here, we sought to explore the perceptions and responses of students to online learning during the pandemic using a cross-sectional study. Electronic questionnaire was used for data collection. Statistical analyses were performed for 1614 valid questionnaires and P < 0.05 was considered statistically significant. Overall, COVID-19 had more effect on female students, such as fear of COVID-19 (2.4 times higher than the number of male students) and length of time spent learning (H = 42.449, P < 0.05). However, the higher the students' grades were, the less the impact of COVID-19. For the style of lessons, all students would prefer shorter lessons (P < 0.05). Female and fifth-grade students were more prefer combined online and face-to-face learning, and male and freshmen students were more likely to prefer face-to-face learning after the pandemic. More than 50% of students thought the main advantage of online learning was convenience, with low efficiency being a disadvantage. The main factors negatively influencing online learning were eyestrain, poor network connections, and poor learning environments at home. In conclusion, synchronous online and face-to-face learning may become more common in future curricula, however the efficiency of online learning and the female students more attentions.

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It is harder to learn a proper name than a common noun in association with a new face, and low-frequency (LF) or rare surnames are harder to learn than high-frequency (HF) or common surnames. A separate body of research has shown that words containing HF phonological components can be easier to retrieve and produce than words with LF phonological components. This study tested for a "downstream" benefit of increased syllable frequency (independent of name frequency) on name-face association learning: surnames with HF first syllables were predicted to be learned more easily than those with LF first syllables. Participants were tasked with learning 5 names with HF first syllables and 5 names with LF first syllables in association with 10 unfamiliar faces over repeated testing rounds with feedback. People learned more names containing HF than LF first syllables, demonstrating a benefit of increased phonological frequency to name learning. Findings support an interactive activation model that accounts for name-face association learning as well as phonological frequency effects on production, along with many other aspects of memory and language.

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Digital learning is becoming increasingly important in the crisis COVID-19 and is widespread in most countries. The proliferation of smart devices and 5G telecommunications systems are contributing to the development of digital learning systems as an alternative to traditional learning systems. Digital learning includes blended learning, online learning, and personalized learning which mainly depends on the use of new technologies and strategies, so digital learning is widely developed to improve education and combat emerging disasters such as COVID-19 diseases. Despite the tremendous benefits of digital learning, there are many obstacles related to the lack of digitized curriculum and collaboration between teachers and students. Therefore, many attempts have been made to improve the learning outcomes through the following strategies: collaboration, teacher convenience, personalized learning, cost and time savings through professional development, and modeling. In this study, facial expressions and heart rate are used to measure the effectiveness of digital learning systems and the level of learners' engagement in learning environments. The results showed that the proposed approach outperformed the known related works in terms of learning effectiveness. The results of this research can be used to develop a digital learning environment.

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The COVID-19 pandemic required adjustments and limitations in university teaching, thereby challenging teaching concepts in anatomy requiring in-person contact, including the gross anatomy course. Therefore, the present study investigates the impact of COVID-19-associated adjustments on students' perception of the gross anatomy course's importance and quality, students' preferred learning setting and outcome, and their motivation to involve themselves in academic activities, including becoming a future peer-teacher of the course. Using paper-based questionnaires in Ulm, Germany, 397 (response rate: 82.3%) students of the winter term of 2020/2021 were surveyed using quantitative and qualitative items, which were compared with cohorts prior to the pandemic. Students reported a higher global rating on course quality during COVID-19 (pre-COVID-19: 5.3 ± 0.9, during-COVID-19: 5.6 ± 0.7, p < 0.001; 1 = very bad, 6 = very good). Students' perceived importance of the gross anatomy course showed a small but significant increase (pre-COVID-19: 4.2 ± 0.6, during-COVID-19: 4.3 ± 0.6, p < 0.001; 1 = strongly disagree, 6 = strongly agree). Students' motivation to apply as a peer-teacher remained stable, nevertheless, they reported less interest in transferring their knowledge to junior students. Finally, students reported that they spent significantly more learning time alone and their examination grades remained unchanged during the pandemic. Astonishingly, despite radical changes of the teaching environment due to COVID-19, students appreciate the offered teaching and highly valued the gross anatomy course.

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