Video lecture format, student technological efficacy, and social presence in online courses

Online platforms are frequently used as an alternative environment for individuals to meet and engage in a variety of activities, like attending courses online. We examined the effect of adding social presence cues in online video lectures and technological efficacy on college students’ perceived learning, class social presence, and perception that the videos aided learning. Participants rated their technological efficacy and completed an online class with video lectures that either included the video (image) of the instructor or not. The interaction between technological efficacy and video manipulation predicted lower ratings of perceived learning, social presence, and video usefulness, particularly for students with lower technological efficacy. A mediated-moderation analysis showed that, the interaction between person (efficacy) and media (instructor image in video vs. no image) predicted greater perceived learning through the mediators of perceived usefulness of videos, class interactivity, and felt comfort in the class.     

Exploring Relationships Between Eye Tracking and Traditional Usability Testing Data

This study explored the relationships between eye tracking and traditional usability testing data in the context of analyzing the usability of Algebra Nation?, an online system for learning mathematics used by hundreds of thousands of students. Thirty-five undergraduate students (20 females) completed seven usability tasks in the Algebra Nation? online learning environment. The participants were asked to log in, select an instructor for the instructional video, post a question on the collaborative wall, search for an explanation of a mathematics concept on the wall, find information relating to Karma Points (an incentive for engagement and learning), and watch two instructional videos of varied content difficulty. Participants’ eye movements (fixations and saccades) were simultaneously recorded by an eye tracker. Usability testing software was used to capture all participants’ interactions with the system, task completion time, and task difficulty ratings. Upon finishing the usability tasks, participants completed the System Usability Scale. Important relationships were identified between the eye movement metrics and traditional usability testing metrics such as task difficulty rating and completion time. Eye tracking data were investigated quantitatively using aggregated fixation maps, and qualitative examination was performed on video replay of participants’ fixation behavior. Augmenting the traditional usability testing methods, eye movement analysis provided additional insights regarding revisions to the interface elements associated with these usability tasks.     

The instructor's gaze guidance in video lectures improves learning

Instructor behaviour is known to affect learning performance, but it is unclear which specific instructor behaviours can optimize learning. We used eye‐tracking technology and questionnaires to test whether the instructor's gaze guidance affected learners' visual attention, social presence, and learning performance, using four video lectures: declarative knowledge with and without the instructor's gaze guidance and procedural knowledge with and without the instructor's gaze guidance. The results showed that the instructor's gaze guidance not only guided learners to allocate more visual attention to corresponding learning content but also increased learners' sense of social presence and learning. Furthermore, the link between the instructor's gaze guidance and better learning was especially strong for participants with a high sense of social connection with the instructor when they learned procedural knowledge. The findings lead to a strong recommendation for educational practitioners: Instructors should provide gaze guidance in video lectures for better learning performance.     

Instructor accents in online education and their effect on learning and attitudes

Reductions in perceptual fluency have been shown to negatively impact attitudes towards learning material, but not learning itself. The current study extends this work to spoken presentations and examines whether the presence of a foreign accent negatively affects learners' experience in an online learning environment. Results indicate that the presence of an instructor accent, consistent with prior work on perceptual fluency, does not impact learning, but does cause learners to rate the instructor as less effective. Further, for those who received accented presentations, changes in participants' attitudes towards both the content area and online instruction were not predicted by learning, but instead their attitude towards the instructor. This suggests that learners in online learning environments with accented narration are potentially miscalibrated, and these biases in judgement could be inappropriately linked to a specific instructor, rather than their success of learning in the field.     

Lecture capture with real‐time rearrangement of visual elements: impact on student performance

The primary goal of this study is to create and test a lecture‐capture system that can rearrange visual elements while recording is still taking place, in such a way that student performance can be positively influenced. The system we have devised is capable of integrating and rearranging multimedia sources, including learning content, the instructor and students' images, into lecture videos that are embedded in a website for students to review after school. The present study employed a two‐group experimental design, with 153 participants (145 females and 8 males) making up an experimental group in which lecture courses were recorded using the new lecture‐capture system, and 149 participants (140 females and 9 males) forming a control group whose lectures were recorded by traditional means. All participants were in the freshman college and studying Introduction to Computer and Information Science in one of six classes, and were randomly assigned to one of the two groups. The participants' midterm examination and final examination scores were collected as indicators of their academic performance, with their mathematics entrance scores used as a pre‐test. The findings obtained from analysis of covariance (ANCOVA) suggest that appropriate rearrangement of visual elements in lecture videos can significantly impact students' learning performance.     

Factors of learner–instructor interaction which predict perceived learning outcomes in online learning environment

Interaction in the online learning environment has been regarded as one of the most critical elements that affect learning outcomes. This study examined what factors in learner–instructor interaction can predict the learner's outcomes in the online learning environment. Learners in K Online University participated by answering the survey, and data from 654 respondents were analysed for this study. Results showed that factors related to instructional interaction predicted perceived learning achievement and satisfaction better than factors related to social interaction. However, it was revealed that social interaction such as social intimacy could negatively affect perceived learning achievement and satisfaction. This study has value because it found factors under learner–instructor interaction which predict perceived learning achievement and satisfaction with empirical evidence.     

Exploring Online Learners' Interactive Dynamics by Visually Analyzing Their Time‐anchored Comments

MOOCs (Massive Open Online Courses) are increasingly prevalent as an online educational resource open to everyone and have attracted hundreds of thousands learners enrolling these online courses. At such scale, there is potentially rich information of learners' behaviors embedded in the interactions between learners and videos that may help instructors and content producers adjust the instructions and refine the online courses. However, the lack of tools to visualize information from interactive data, including messages left to the videos at particular timestamps as well as the temporal variations of learners' online participation and perceived experience, has prevented people from gaining more insights from video‐watching logs. In this paper, we focus on extracting and visualizing useful information from time‐anchored comments that learners left to specific time points of the videos when watching them. Timestamps as a kind of metadata of messages can be useful to recover the interactive dynamics of learners occurring around the videos. Therefore, we present a visualization system to analyze and categorize time‐anchored comments based on topics and content types. Our system integrates visualization methods of temporal text data, namely ToPIN and ThemeRiver, which can help people understand the quality and quantity of online learners' feedback and their states of learning. To evaluate the proposed system, we visualized time‐anchored commenting data from two online course videos, and conducted two user studies participated by course instructors and third‐party educational evaluators. The results validate the usefulness of the approach and show how the quantitative and qualitative visualizations can be used to gain interesting insights around learners' online learning behaviors.     

Using eye-movement modelling examples to improve critical reading of multiple webpages on a conflicting topic

Interventions to promote students' source evaluations have used various methods designed for the classroom context. In the present study, we tested an approach that is easily adaptable to online courses, based on eye movement modelling examples (EMME), that is, short videos displaying an expert student's eye gaze while s/he reads multiple pages on the Internet to learn about a conflicting topic. Using an eye-tracking methodology in a pre–post design, we analysed how an intervention using EMME changed students' attention to source information, and how this processing affected their learning. EMME increased participants' attention to the search engine results page, author information and decreased attention of texts from untrustworthy pages. In addition, EMME increased the number of participants who cited at least one document source at post-test. We discuss the potential benefits and limitations of EMME in teaching complex literacy strategies, and the importance of measuring processing data in educational research studies.     

Does instructor's image size in video lectures affect learning outcomes?

One of the most commonly used forms of video lectures is a combination of an instructor's image and accompanying lecture slides as a picture‐in‐picture. As the image size of the instructor varies significantly across video lectures, and so do the learning outcomes associated with this technology, the influence of the instructor's image size should be evaluated. This study tested the effect of image size of the instructor on learners' experience of social presence, cognitive load, learning performance and satisfaction. In the study, 87 Chinese undergraduates were randomly assigned to view a video lecture with a small image of the instructor, with a medium image size of the instructor or with a large image of the instructor. The results of analyses of variances and analysis of covariance suggested that learners perceived the same level of social presence and cognitive load across video lectures with different image sizes of the instructor; learners who watched the video lecture with the small image of the instructor learned better than those who watched the video lectures with the medium and the large images of the instructors. Furthermore, learners who watched the video lecture with the small image and medium image of the instructor experienced more learning satisfaction. The findings highlight the importance of image size of the instructor in video lecture learning.     

Summarization of Visual Content in Instructional Videos

In instructional videos of chalk board presentations, the visual content refers to the text and figures written on the boards. Existing methods on video summarization are not effective for this video domain because they are mainly based on low-level image features such as color and edges. In this work, we present a novel approach to summarizing the visual content in instructional videos using middle-level features. We first develop a robust algorithm to extract content text and figures from instructional videos by statistical modelling and clustering. This algorithm addresses the image noise, nonuniformity of the board regions, camera movements, occlusions, and other challenges in the instructional videos that are recorded in real classrooms. Using the extracted text and figures as the middle level features, we retrieve a set of key frames that contain most of the visual content. We further reduce content redundancy and build a mosaicked summary image by matching extracted content based on K-th Hausdorff distance and connected component decomposition. Performance evaluation on four full-length instructional videos shows that our algorithm is highly effective in summarizing instructional video content.     

Investigating the relationships among instructional strategies and learning styles in online environments

This exploratory study tests the assertion that instructional strategies that match field-dependence status of students are most effective. The study conducted with 12 graduate students registered in a graduate level online course. An online version of the Psychological Differentiation Inventory was used to measure the field-dependence status of students. Students’ perceived learning outcomes, their effort and involvement, and level of interaction that they perceived in online course module were measured through an online questionnaire. Results suggested that matches between students’ learning styles and instructional strategies did not affect learner perception of their own learning outcomes, level of effort and involvement, and level of interactions in the course. Data also indicated that no single instructional strategy, among three instructional strategies tested, emerged as superior for high and low field-dependent online students.     

Online web video topic detection and tracking with semi-supervised learning

With the pervasiveness of online social media and rapid growth of web data, a large amount of multi-media data is available online. However, how to organize them for facilitating users’ experience and government supervision remains a problem yet to be seriously investigated. Topic detection and tracking, which has been a hot research topic for decades, could cluster web videos into different topics according to their semantic content. However, how to online discover topic and track them from web videos and images has not been fully discussed. In this paper, we formulate topic detection and tracking as an online tracking, detection and learning problem. First, by learning from historical data including labeled data and plenty of unlabeled data using semi-supervised multi-class multi-feature method, we obtain a topic tracker which could also discover novel topics from the new stream data. Second, when new data arrives, an online updating method is developed to make topic tracker adaptable to the evolution of the stream data. We conduct experiments on public dataset to evaluate the performance of the proposed method and the results demonstrate its effectiveness for topic detection and tracking.     

Motivational beliefs and perceptions of instructional quality: predicting satisfaction with online training*

Abstract Many would agree that learning on the Web – a highly autonomous learning environment – may be difficult for individuals who lack motivation and self‐regulated learning skills. Using a social cognitive view of academic motivation and self‐regulation, the objective of the present study was to investigate the relations between students' motivational beliefs, their perceptions of the learning environment and their satisfaction with a self‐paced, online course. Service academy undergraduates (n = 646) completed a questionnaire following online training. Pearson correlations indicate that task value, self‐efficacy and perceived instructional quality were significantly positively related to each other and to students' overall satisfaction with the self‐paced, online course. Additionally, results from a three‐step hierarchical regression reveal that task value, self‐efficacy and instructional quality were significant positive predictors of students' satisfaction; the final regression model accounted for approximately 54% of the variance in the outcome measure. These findings support and extend prior research in traditional classrooms and online education in university settings, indicating that military students' motivational beliefs about a learning task and their perceptions of instructional quality are related, in important ways, to their overall satisfaction with online instruction. Educational implications and suggestions for future research are discussed.     

The impact of the social context on value and expectancy beliefs in an online graduate program: The role of social presence

This study examines the influence of perceived social presence on online graduate students' value and expectancy beliefs. Forty-nine participants enrolled in an online teacher leadership graduate program completed questionnaires that measured perceived social presence and value and expectancy beliefs. A series of simple linear regression analyses revealed that social presence positively predicted students' value for online learning. Social presence did not predict participants' expectations of future success in teacher leadership. Results partially supported the assumption of the expectancy-value model that motivational beliefs are influenced by the information students receive from social partners. Moreover, the study tested and confirmed the application of the model in online settings and for students pursuing graduate education.     

Advance on large scale near-duplicate video retrieval

Emerging Internet services and applications attract increasing users to involve in diverse video-related activities, such as video searching, video downloading, video sharing and so on. As normal operations, they lead to an explosive growth of online video volume, and inevitably give rise to the massive near-duplicate contents. Near-duplicate video retrieval (NDVR) has always been a hot topic. The primary purpose of this paper is to present a comprehensive survey and an updated reviewof the advance on large-scaleNDVR to supply guidance for researchers. Specifically, we summarize and compare the definitions of near-duplicate videos (NDVs) in the literature, analyze the relationship between NDVR and its related research topics theoretically, describe its generic framework in detail, investigate the existing state-of-the-art NDVR systems. Finally, we present the development trends and research directions of this topic.     

Effects of prior knowledge and joint attention on learning from eye movement modelling examples

Eye movement modelling examples (EMMEs) are instructional videos of a model's demonstration and explanation of a task that also show where the model is looking. EMMEs are expected to synchronize students' visual attention with the model's, leading to better learning than regular video modelling examples (MEs). However, synchronization is seldom directly tested. Moreover, recent research suggests that EMMEs might be more effective than ME for low prior knowledge learners. We therefore used a 2 × 2 between-subjects design to investigate if the effectiveness of EMMEs (EMMEs/ME) is moderated by prior knowledge (high/low, manipulated by pretraining), applying eye tracking to assess synchronization. Contrary to expectations, EMMEs did not lead to higher learning outcomes than ME, and no interaction with prior knowledge was found. Structural equation modelling shows the mechanism through which EMMEs affect learning: Seeing the model's eye movements helped learners to look faster at referenced information, which was associated with higher learning outcomes.     

Sage,guide, both,or even more? An examination of instructor activity in online MBA courses

This study examined faculty characteristics and behaviors in 46 MBA courses conducted over a two-year period. We found that both formal instructor activities, referred to in the online learning literature as teaching presence, and informal instructor activities, known as immediacy behaviors, were positive predictors of student perceived learning and satisfaction with the educational delivery medium. We also found that instructor login intensity, the average amount of time spent per login session, was a negative predictor of perceived learning. Collectively, these findings suggest the need for instructors to structure and organize their courses beforehand so they can focus on efficient engagement with their students while the class is in session. Although teaching presence and instructor immediacy were significant predictors of delivery medium satisfaction, they explained only 6% of the variance. This finding should help instructors avoid taking unnecessary responsibility for students’ attitudes toward online learning. The paper concludes with a discussion of implications for training of online instructors and the appropriate use of multilevel analytical tools in online learning and education research.     

Effects on learning of time spent by university students attending lectures and/or watching online videos

We apply Carroll's model of school learning, which theorizes about the relationship between time and learning, to motivate the design of a large, first‐year, university mathematics course, where students have the choice to attend lectures and/or watch online videos. The theoretical model informs how the course and resources are designed in order to assist students to spend the time they need to master a task in an efficient manner. We examine the relationship between learning and time spent on lectures and/or videos, by analysing data collected on lecture attendance, videos accessed, and mathematical achievement, prior to, and at the end of, the course. Findings show that students use videos as either a complement to, or substitute for, the lecture, and time spent using either or both resources has a significant impact on learning.     

多媒体内容理解的研究现状与展望

跨媒体网络视频热点话题检测成为新的研究热点.然而,描述视频的文本信息较少,使得文本语义特征空间稀疏,导致文本语义特征间关联强度较弱,增加了挖掘热点话题的难度.现有方法主要通过视觉信息丰富文本语义特征空间.然而,由于视觉与文本信息间的异构性,导致同一话题下文本与视觉语义特征差异较大,这进一步降低了同一话题下文本语义间的关联强度,也给跨媒体网络视频热点话题检测带来巨大挑战.因此,提出一种新的跨媒体语义关联增强方法.首先,通过双层注意力,从单词和句子2个级别捕捉文本核心语义特征;其次,通过理解视觉内容,生成大量与视频内容高度相关的文本描述,丰富文本语义空间;然后,分别通过文本语义相似性和视觉语义相似性,构建文本语义图和视觉语义图,并构造时间衰减函数,从时间维度建立跨媒体数据间的相关性,以此增强文本与视觉语义间的关联强度,平滑地将2种语义图融合为混合语义图,实现跨媒体语义互补;最后,通过图聚类方法检测出热点话题.大量实验结果表明,提出的模型优于现有方法.

     

Exploring the cognitive loads of high-school students as they learn concepts in web-based environments

This study measured high-school learners' cognitive load as they interacted with different web-based curriculum components, and examined the interactions between cognitive load and web-based concept learning. Participants in this study were 105 11th graders from an academic senior high school in Taiwan. An online, multimedia curriculum on the topic of global warming, which lasted for four weeks, provided the learning context. After students worked through the curriculum, their feelings about the degree of mental effort that it took to complete the learning tasks were measured by self-report on a 9-point Likert scale. An online test and the flow-map method were applied to assess participants' concept achievements. The results showed that curriculum components such as scientific articles, online notebooks, flash animations and the online test induced a relatively high cognitive load, and that a lower cognitive load resulted in better concept achievement. Also, students appeared to adopt different learning approaches that were corresponding to different levels of cognitive load.