Attention to the model's face when learning from video modeling examples in adolescents with and without autism spectrum disorder

We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate whether we would replicate this finding in adolescents (prevocational education) and to establish how adolescents with autism spectrum disorder, who have been found to look less at faces generally, would process video examples in which the model's face is visible. Results showed that typically developing adolescents who did see the model's face paid significantly less attention to the task area than typically developing adolescents who did not see the model's face. Adolescents with autism spectrum disorder paid less attention to the model's face and more to the task demonstration area than typically developing adolescents who saw the model's face. These differences in viewing behavior, however, did not affect learning outcomes. This study provides further evidence that seeing the model's face in video examples affects students' attention but not their learning outcomes

Do social cues in instructional videos affect attention allocation, perceived cognitive load, and learning outcomes under different visual complexity conditions?

Background:There are only few guidelines on how instructional videos should be designed to optimize learning. Recently, the effects of social cues on attention allocation and learning in instructional videos have been investigated. Due to inconsistent results, it has been suggested that the visual complexity of a video influences the effect of social cues on learning.Objectives:Therefore, this study compared the effects of social cues (i.e., gaze & gesture) in low and high visual complexity videos on attention, perceived cognitive load,and learning outcomes.Methods:Participants (N=71) were allocated to a social cue or no social cue condition and watched both a low and a high visual complexity video. After each video, participants completed a knowledge test.Results and Conclusions: Results showed that participants looked faster at referenced information and had higher learning outcomes in the low visual complexity condition. Social cues did not affect any of the dependent variables, except when including prior knowledge in the analysis: In this exploratory analysis, the inclusion of gaze and gesture cues in the videos did lead to better learning outcomes.Takeaways: Our results show that the visual complexity of instructional videos and prior knowledge are important to take into account in future research on attention and learning from instructional videos

Systematic Review of COVID Spillover and Online Education Pedagogy

This paper has touched one of the most critical area affected due to pandemic situation created by the COVID-19 and its powerful spillover effect on education sector by customizing education pedagogy. Earlier researchers have studied online education separately, whereas this paper discussed the natural transition and systematic review of upsurge of e-learning. The objective of this paper is to make the systematic review of COVID spillover and transition towards e-learning education pedagogy through theoretical framework. The study makes systematic review of switchover towards e-learning and spillover effect of COVID-19 and customization of the education pedagogy. In this study, past literature has been utilized to make critical analysis of spillover effect of COVID-19 and impact on education pedagogy by creation of prepositions. The findings of the study reveal that in the exceptional circumstances of COVID-19, e-learning transition has taken place from conventional to e-learning modules. All over the world, countries have shifted towards online education by schooling out but classes in campaign ignited by Chinese government. The same has also been replicated in other countries of the world during COVID-19

Do social cues in instructional videos affect attention allocation, perceived cognitive load, and learning outcomes under different visual complexity conditions?

Background: There are only few guidelines on how instructional videos should be designed to optimize learning. Recently, the effects of social cues on attention allocation and learning in instructional videos have been investigated. Due to inconsistent results, it has been suggested that the visual complexity of a video influences the effect of social cues on learning. Objectives: Therefore, this study compared the effects of social cues (i.e., gaze & gesture) in low and high visual complexity videos on attention, perceived cognitive load, and learning outcomes. Methods: Participants (N = 71) were allocated to a social cue or no social cue condition and watched both a low and a high visual complexity video. After each video, participants completed a knowledge test. Results and Conclusions: Results showed that participants looked faster at referenced information and had higher learning outcomes in the low visual complexity condition. Social cues did not affect any of the dependent variables, except when including prior knowledge in the analysis: In this exploratory analysis, the inclusion of gaze and gesture cues in the videos did lead to better learning outcomes. Takeaways: Our results show that the visual complexity of instructional videos and prior knowledge are important to take into account in future research on attention and learning from instructional videos

Shifting online: 12 tips for online teaching derived from contemporary educational psychology research

Background: As a result of the COVID-19 pandemic, many teachers found themselves making a rapid and often challenging shift from in-person classroom teaching to teaching in an online environment. As teachers continue to learn about working in this new environment, research in cognitive and learning sciences, specifically findings from cognitive load theory and related areas, can provide meaningful strategies for teaching in this ‘new normal’. Objectives: This paper describes 12 tips derived from contemporary research in educational psychology, focusing particularly on empirically supported strategies that teachers may apply in their online classroom to ensure that learning is optimized. Implications for Practice: These strategies are generalizable across age groups and learning areas, and are categorized into one of two themes: approaches to optimize the design of online learning materials, and instructional strategies to support student learning. A discussion follows, outlining how teachers may apply these strategies in different contexts, with a brief overview of emerging efforts that aim to bridge cognitive load theory and self-regulated learning research

Dynamic adaptation of streamed real-time E-learning videos over the internet

Even though the e-learning is becoming increasingly popular in the academic environment, the quality of synchronous e-learning video is still substandard and significant work needs to be done to improve it. The improvements have to be brought about taking into considerations both: the network requirements and the psycho- physical aspects of the human visual system. One of the problems of the synchronous e-learning video is that the head-and-shoulder video of the instructor is mostly transmitted. This video presentation can be made more interesting by transmitting shots from different angles and zooms. Unfortunately, the transmission of such multi-shot videos will increase packet delay, jitter and other artifacts caused by frequent changes of the scenes. To some extent these problems may be reduced by controlled reduction of the quality of video so as to minimise uncontrolled corruption of the stream. Hence, there is a need for controlled streaming of a multi-shot e-learning video in response to the changing availability of the bandwidth, while utilising the available bandwidth to the maximum. The quality of transmitted video can be improved by removing the redundant background data and utilising the available bandwidth for sending high-resolution foreground information. While a number of schemes exist to identify and remove the background from the foreground, very few studies exist on the identification and separation of the two based on the understanding of the human visual system. Research has been carried out to define foreground and background in the context of e-learning video on the basis of human psychology. The results have been utilised to propose methods for improving the transmission of e-learning videos. In order to transmit the video sequence efficiently this research proposes the use of Feed- Forward Controllers that dynamically characterise the ongoing scene and adjust the streaming of video based on the availability of the bandwidth. In order to satisfy a number of receivers connected by varied bandwidth links in a heterogeneous environment, the use of Multi-Layer Feed-Forward Controller has been researched. This controller dynamically characterises the complexity (number of Macroblocks per frame) of the ongoing video sequence and combines it with the knowledge of availability of the bandwidth to various receivers to divide the video sequence into layers in an optimal way before transmitting it into network. The Single-layer Feed-Forward Controller inputs the complexity (Spatial Information and Temporal Information) of the on-going video sequence along with the availability of bandwidth to a receiver and adjusts the resolution and frame rate of individual scenes to transmit the sequence optimised to give the most acceptable perceptual quality within the bandwidth constraints. The performance of the Feed-Forward Controllers have been evaluated under simulated conditions and have been found to effectively regulate the streaming of real-time e-learning videos in order to provide perceptually improved video quality within the constraints of the available bandwidth

The Effects of Augmented Reality-supported Instruction in Tertiary-level Medical Education

A significant body of the literature has documented the potential of Augmented Reality (AR) in education, but little is known about the effects of AR-supported instruction in tertiary-level Medical Education (ME). This quasi-experimental study compares a traditional instructional approach with supplementary online lecture materials using digital handout notes with a control group (n = 30) and an educational AR application with an experimental group (n = 30) to investigate any possible added-value and gauge the impact of each approach on students' academic performance and training satisfaction. This study's findings indicate considerable differences in both academic performance and training satisfaction between the two groups. The participants in the experimental group performed significantly better than their counterparts, an outcome which is also reflected in their level of training satisfaction through interacting and viewing 3D multimedia content. This study contributes by providing guidelines on how an AR-supported intervention can be integrated into ME and provides empirical evidence on the benefits that such an approach can have on students' academic performance and knowledge acquisition

The effects of augmented reality-supported instruction in tertiary-level medical education

A significant body of the literature has documented the potential of Augmented Reality (AR) in education, but little is known about the effects of AR-supported instruction in tertiary-level Medical Education (ME). This quasi-experimental study compares a traditional instructional approach with supplementary online lecture materials using digital handout notes with a control group (n = 30) and an educational AR application with an experimental group (n = 30) to investigate any possible added-value and gauge the impact of each approach on students' academic performance and training satisfaction. This study's findings indicate considerable differences in both academic performance and training satisfaction between the two groups. The participants in the experimental group performed significantly better than their counterparts, an outcome which is also reflected in their level of training satisfaction through interacting and viewing 3D multimedia content. This study contributes by providing guidelines on how an AR-supported intervention can be integrated into ME and provides empirical evidence on the benefits that such an approach can have on students' academic performance and knowledge acquisition. Practitioner notes What is already known about this topic Several studies have applied various Augmented Reality (AR) applications across different learning disciplines. The effects of AR on students' perceptions and achievements in higher education contexts is well-documented. Despite the increasing use of AR-instruction in Medical Education (ME), there has been no explicit focus on AR's effects on students' academic performance and satisfaction. What this paper adds This quasi-experimental study compares the academic performance and training satisfaction of students in an experimental group (AR) and a control group (handout notes). This study provides instructional insights into, and recommendations that may help students achieve better academic performance in AR-supported ME courses. The experimental group reported greater training satisfaction than their counterparts. Implications for practice and policy Students who followed the AR-supported instruction achieved better academic performance that those in the control group. AR-supported interventions encourage active learning and lead to significant performance improvement. The experimental group outperformed the control group in academic performance and training satisfaction measurements, despite the lower experimental group's lower pre-test performance scores

Challenges Faced by the Teachers and Students in Online Learning during COVID-19

Most of the educational institutions in Pakistan are based on traditional method of learning and teaching. Although various institutions are now converting the learning methods from traditional to technology based online learning, yet a lot of work is to be done. The sudden outbreak of Pandemic disease Covid-19 has totally changed the learning and teaching system. Many educational institutions that were based on traditional methods of learning and teaching have to shift entirely on online learning and teachings. The main objective of the study was to highlight the challenges faced by students and teachers during Covid-19 in learning and teachings at undergraduate and graduate levels. For this, students and teachers of four universities from Southern area were selected conveniently. A self- developed closed ended questionnaire for teachers and students was used to collect data. The questionnaire was fully validated and piloted to make it the best for use.  The results of the research indicated that the students and teachers faced a lot of problems during the online learning and teaching. These included problems related internet connectivity, login, economical problems, time management etc. On the basis of findings, it is recommended to introduce course relate the usage of information technology or conduct special training before this activity of online classes.&nbsp

University catalog, 2016-2017

The catalog is a comprehensive reference for your academic studies. It includes a list of all degree programs offered at MU, including bachelors, masters, specialists, doctorates, minors, certificates, and emphasis areas. It details the university wide requirements, the curricular requirements for each program, and in some cases provides a sample plan of study. The catalog includes a complete listing and description of approved courses. It also provides information on academic policies, contact information for supporting offices, and a complete listing of faculty members. -- Page 3