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The purpose of this paper, building on the media richness theory (MRT), is to propose that while communicating product information via streaming video should enhance outcome measures, such an enhancement will be evident mainly for users with equivocal, latent goals (i.e. recreational browsing) rather than for those with less equivocal, concrete goals (i.e. the search of a specific product).

The experiment involved 337 potential online consumers in Canada, and had full factorial design with four conditions (two methods to communicate product information: textual vs streaming video, and two goals: product searching vs recreational browsing). Analysis of covariance was used to test the hypotheses.

The results lent support to the hypotheses. The perceived information quality, trusting competence, and arousal for participants with recreational browsing goals were significantly affected when product information where communicated using streaming video. For participants with concrete goals (product searchers), the traditional textual method was as effective as the streaming video method.

The findings entice practitioners to use rich media such as the streaming video method to communicate online information predominantly for users with experiential browsing goals, and to use lean media for users with less equivocal, concrete goals.

The results contribute to the sparse literature that underscores the key role of user goal in shaping the effectiveness of online information. The results provide empirical support to the prediction of MRT that the use of rich media to communicate information is advantageous for users with latent, equivocal goals.

High-efficiency video coding (HEVC) is the latest video coding standard that has better coding efficiency than the H.264/advanced video coding (AVC) standard. The purpose of this paper is to design and develop an effective block search mechanism for the video compression-HEVC standard such that the developed compression standard is applied for the communication applications.

In the proposed method, an rate-distortion (RD) trade-off, named regressive RD trade-off is used based on the conditional autoregressive value at risk (CaViar) model. The motion estimation (ME) is based on the new block search mechanism, which is developed with the modification in the Ordered Tree-based Hex-Octagon (OrTHO)-search algorithm along with the chronological Salp swarm algorithm (SSA) based on deep recurrent neural network (deepRNN) for optimally deciding the shape of search, search length of the tree and dimension. The chronological SSA is developed by integrating the chronological concept in SSA, which is used for training the deep RNN for ME.

The competing methods used for the comparative analysis of the proposed OrTHO-search based RD + chronological-salp swarm algorithm (RD + C-SSA) based deep RNN are support vector machine (SVM), fast encoding framework, wavefront-based high parallel (WHP) and OrTHO-search based RD method. The proposed video compression method obtained a maximum peak signal-to-noise ratio (PSNR) of 42.9180 dB and a maximum structural similarity index measure (SSIM) of 0.9827.

In this research, an effective block search mechanism was developed with the modification in the OrTHO-search algorithm along with the chronological SSA based on deepRNN for the video compression-HEVC standard.

Two common methods in community settings of assessing program fidelity, a critical implementation component for program effectiveness, are video and audio recordings of sessions. This paper aims to examine how these two methods compared when used for a home-based behavioral parenting-training model (SafeCare®).

Twenty-five SafeCare video-recorded sessions between home visitors and parents were scored by trained raters either using the video or audio-only portions of recordings. Sessions were coded using fidelity checklists, with items (n = 33) classified as one of two fidelity aspects, content [delivery of program components (n = 15)], or process [communication and rapport building (n = 11)]. Seven items were considered to overlap between constructs. Items were coded as having been done or not done appropriately. Coders rated items as “technological limitation” when scoring methods hindered coding. Analyses compared percent agreement and disagreement between audio and video coders.

Overall agreement between coders was 72.12%. Levels of agreement were higher for content items (M = 80.89%, SD = 19.68) than process items (58.54%, SD = 34.41). Disagreements due to technology limitations among audio coders were noted among 15 items; particularly, higher levels of disagreement were seen among process items (42.42%) than content items (9.64%).

Compared to video, fidelity monitoring via audio recordings was associated with some loss of process-related fidelity. However, audio recordings could be sufficient with supplements such as participant surveys, to better capture process items. Research should also examine how content and process fidelity relate to changes in family behavior to further inform optimal fidelity monitoring methods for program use.

The purpose of this paper is to examine the determinants of learners' satisfaction with a new blended learning method, namely online video presentations.

The study tests the proposed model using responses from 353 students who were exposed to the new method. Regression analysis was used to test the hypotheses.

The results show that both the perceived social (e.g. reduction in comparison bias) and utilitarian (e.g. presentation originality) benefits increase satisfaction with the online video presentation method, from both the creator's and the learner's perspectives.

This study provides several guidelines to instructors employing blended learning methods, as well as designers of platforms that enable blended learning.

This study provides a model to understand the determinants of learners' satisfaction with a new blended learning method. It looks at these determinants from both the content creators' perspective and the content viewer's perspective.

This chapter presents a novel method for using PechaKucha presentations to generate and analyze participant-generated video data. As a data source, participatory video (PV) differs from ethnographic or archival video by relying on participants to tell their own stories. As a presentation technique, PechaKucha produces six-minute-and-forty-second, narrated slideshow presentations. The slideshows or recordings from live PechaKucha presentations are a dense form of PV that is easier to code and analyze than traditional sources of PV. This chapter describes the procedures to capture and analyze PechaKucha-based PV and illustrates considerations for researchers who plan to use PV to gather data.

The global call to ‘leave-no-one behind’ cannot be achieved without tacking the intractable social issues faced by the most excluded people. There is increasing interest in using visual methodologies for participatory research in contexts of marginalisation, because they offer the potential to generate knowledge from people’s lived experience, which can reveal subjective, emotional, and contextual aspects missed by other methods; alongside the means for action through showing outputs to external audiences. The challenge is that the perspectives of those in highly inequitable and unaccountable contexts are – by definition – rarely articulated and often neglected. The author thus begins by assuming that there are unavoidable tensions in using visual methods; between perpetuating marginalisation by inaction, which is ethically questionable; and the necessary risks in bringing unheard views to public attention. Many experienced practitioners have called for a situated approach to visual methods ethics (Clark, Prosser, & Wiles, 2010; Gubrium, Hill, & Flicker 2014; Shaw, 2016). What is less clear is what this means for those wanting to apply this practically. In this chapter, the author addresses this gap through the exemplar of participatory video with marginalised groups. Drawing on cases from Kenya, India, Egypt, and South Africa, the author contributes a range of tried-and-tested strategies for navigating the biggest concerns such as informing consent; and the tensions between respecting autonomy and building inclusion, and between anonymity and supporting participant’s expressive agency. Through this, the author provides a resource for researchers, including prompts for critical reflection about how to generate solutions to visual ethical dilemmas in context.

Despite the actual prevalence of diverse types of multimedia information, research on video news is still in an early stage. Improving the accessibility of video news seems worth investigating, therefore, the purpose of this paper is to present a new combination mode of video news text clustering and selection. This method is useful for sorting out and classifying various types of news videos and media texts based on sentiment analysis.

A novel system is proposed, whereby video news are identified and categorized into good or bad ones via the authors' suggested Hidden Markov Model (HMM) and Support Vector Machine (SVM) hybrid learning method. Actually, an exploratory video news sentiment analysis case study, conducted on various news databases, has proven that the feature‐selection‐combining method, encompassing the Information Gain (IG), Mutual Information (MI) and CHI‐statistic (CHI), performs the best classification, which testifies and highlights the designed framework's value.

In fact, the system turns out to be applicable to several areas, especially video news, where annotation and personal perspectives affect the accuracy aspect.

The present work shows the way for further research pertaining to the personal attitudes and the application of different linguistic techniques during the classification.

The achieved results are so promising, encouraging and satisfactory, that they highlight the originality and efficiency of the authors' approach as an effective tool enabling to secure an easy access to video news and multi‐media texts.

English education researchers have used video annotation to connect theory to practice and to encourage prospective secondary English teachers (PSETs) to reflectively evaluate their own and others’ teaching. This study aimed to examine whether and how PSETs’ annotations of their own and others’ teaching videos reveal (dis)connections between visions of English teaching valued in methods courses and those practiced in local school field placements.

Examination of 538 annotations on 18 lesson videos – recorded in a university teaching-methods course and in local secondary classrooms by 12 PSETs in a rural, northeastern US teacher-preparation program – revealed what kinds of practices PSETs evaluated and with whom they identified (student or teacher) as they made those evaluations.

Annotations from two PSETs illustrate a trend in the larger data sets: PSETs’ annotations expressed pedagogical values that differed and sometimes conflicted according to their identification with the role of student or of teacher. PSETs’ preferences as students were often superseded by visions of what one must do/be in the secondary English classroom.

This study identifies tensions among PSETs’ annotations that corresponded to their identifications with the role of student or of teacher but does not explore whether and how they reconciled these tensions, or how they might affect student learning. Future research might explore how PSETs negotiate contradictions in their pedagogical preferences as they annotate their own and others’ teaching videos.

English teacher educators who use video-based methods might attend to whether and how such assignments/activities position PSETs as students or as teachers in viewing teaching videos.

PSETs may value different and even conflicting pedagogical practices, regardless of setting and despite their own experiences, based on their identifications with the role of student or of teacher. These identifications may allow them to compartmentalize visions of teaching that might otherwise come into productive conflict.

Video summarisation is one of the most active fields in content‐based video retrieval research. A new video summarisation scheme is proposed by this paper based on socially generated temporal tags.

To capture users' collaborative tagging activities the proposed scheme maintains video bookmarks, which contain some temporal or positional information about videos, such as relative time codes or byte offsets. For each video all the video bookmarks collected from users are then statistically analysed in order to extract some meaningful key frames (the video equivalent of keywords), which collectively constitute the summary of the video.

Compared with traditional video summarisation methods that use low‐level audio‐visual features, the proposed method is based on users' high‐level collaborative activities, and thus can produce semantically more important summaries than existing methods.

It is assumed that the video frames around the bookmarks inserted by users are informative and representative, and therefore can be used as good sources for summarising videos.

Folksonomy, commonly called collaborative tagging, is a Web 2.0 method for users to freely annotate shared information resources with keywords. It has mostly been used for collaboratively tagging photos (Flickr), web site bookmarks (Del.icio.us), or blog posts (Technorati), but has never been applied to the field of automatic video summarisation. It is believed that this is the first attempt to utilise users' high‐level collaborative tagging activities, instead of low‐level audio‐visual features, for video summarisation.

Visual ethnographic methods are increasingly popular in social science research. Much has been published on their design and use (e.g. Banks, 2001; Pink, 2001; van Leeuwen & Jewitt, 2001). Yet little has been written on using video in in-depth interviews, or how such video-interviews might differ from tape-recorded interviews. In this chapter I discuss the video interview, as developed in my research about gender in the sensory home,¹ to reflect on the nature of the ethnographic knowledge about everyday life and experience this method produces. I focus particularly on informants’ uses of narrative as a vehicle for self-representation that reveals and conceals. Video invites informants to produce narratives that interweave visual and verbal representation. In doing so they reference familiar everyday narratives and practices that are in part visual. Here I discuss how three narratives – which I shall call the “Hello magazine,” “estate agent” and “self-analysis” narratives – were developed in an audiovisual research context.²