How Video Lecture Capture affects Student Engagement in a University Computer Programming Course: Attendance, Video Viewing Behaviours and Student Attitudes

Introduction
The use of video capture of lectures in Higher Education is not a recent occurrence with web based learning technologies including digital recording of live lectures becoming increasing commonly offered by universities throughout the world (Holliman and Scanlon, 2004). However in the past decade the increase in technical infrastructural provision including the availability of high speed broadband has increased the potential and use of videoed lecture capture. This had led to a variety of lecture capture formats including pod casting, live streaming or delayed broadcasting of whole or part of lectures.
Additionally in the past five years there has been a significant increase in the popularity of online learning, specifically via Massive Open Online Courses (MOOCs) (Vardi, 2014). One of the key aspects of MOOCs is the simulated recording of lecture like activities. There has been and continues to be much debate on the consequences of the popularity of MOOCs, especially in relation to its potential uses within established University programmes.
There have been a number of studies dedicated to the effects of videoing lectures.
The clustered areas of research in video lecture capture have the following main themes:
• Staff perceptions including attendance, performance of students and staff workload
• Reinforcement versus replacement of lectures
• Improved flexibility of learning
• Facilitating engaging and effective learning experiences
• Student usage, perception and satisfaction
• Facilitating students learning at their own pace
Most of the body of the research has concentrated on student and faculty perceptions, including academic achievement, student attendance and engagement (Johnston et al, 2012).
Generally the research has been positive in review of the benefits of lecture capture for both students and faculty. This perception coupled with technical infrastructure improvements and student demand may well mean that the use of video lecture capture will continue to increase in frequency in the next number of years in tertiary education. However there is a relatively limited amount of research in the effects of lecture capture specifically in the area of computer programming with Watkins 2007 being one of few studies . Video delivery of programming solutions is particularly useful for enabling a lecturer to illustrate the complex decision making processes and iterative nature of the actual code development process (Watkins et al 2007). As such research in this area would appear to be particularly appropriate to help inform debate and future decisions made by policy makers.
Research questions and objectives
The purpose of the research was to investigate how a series of lecture captures (in which the audio of lectures and video of on-screen projected content were recorded) impacted on the delivery and learning of a programme of study in an MSc Software Development course in Queen’s University, Belfast, Northern Ireland. The MSc is conversion programme, intended to take graduates from non-computing primary degrees and upskill them in this area. The research specifically targeted the Java programming module within the course. It also analyses and reports on the empirical data from attendances and various video viewing statistics. In addition, qualitative data was collected from staff and student feedback to help contextualise the quantitative results.
Methodology, Methods and Research Instruments Used
The study was conducted with a cohort of 85 post graduate students taking a compulsory module in Java programming in the first semester of a one year MSc in Software Development. A pre-course survey of students found that 58% preferred to have available videos of “key moments” of lectures rather than whole lectures. A large scale study carried out by Guo concluded that “shorter videos are much more engaging” (Guo 2013). Of concern was the potential for low audience retention for videos of whole lectures.
The lecturers recorded snippets of the lecture directly before or after the actual physical delivery of the lecture, in a quiet environment and then upload the video directly to a closed YouTube channel. These snippets generally concentrated on significant parts of the theory followed by theory related coding demonstration activities and were faithful in replication of the face to face lecture. Generally each lecture was supported by two to three videos of durations ranging from 20 – 30 minutes.
Attendance
The MSc programme has several attendance based modules of which Java Programming was one element. In order to assess the consequence on attendance for the Programming module a control was established. The control used was a Database module which is taken by the same students and runs in the same semester.
Access engagement
The videos were hosted on a closed YouTube channel made available only to the students in the class. The channel had enabled analytics which reported on the following areas for all and for each individual video; views (hits), audience retention, viewing devices / operating systems used and minutes watched.
Student attitudes
Three surveys were taken in regard to investigating student attitudes towards the videoing of lectures. The first was before the start of the programming module, then at the mid-point and subsequently after the programme was complete.
The questions in the first survey were targeted at eliciting student attitudes towards lecture capture before they had experienced it in the programme. The midpoint survey gathered data in relation to how the students were individually using the system up to that point. This included feedback on how many videos an individual had watched, viewing duration, primary reasons for watching and the result on attendance, in addition to probing for comments or suggestions. The final survey on course completion contained questions similar to the midpoint survey but in summative view of the whole video programme.
Conclusions and Outcomes
The study confirmed findings of other such investigations illustrating that there is little or no effect on attendance at lectures. The use of the videos appears to help promote continual learning but they are particularly accessed by students at assessment periods. Students respond positively to the ability to access lectures digitally, as a means of reinforcing learning experiences rather than replacing them. Feedback from students was overwhelmingly positive indicating that the videos benefited their learning. Also there are significant benefits to part recording of lectures rather than recording whole lectures. The behaviour viewing trends analytics suggest that despite the increase in the popularity of online learning via MOOCs and the promotion of video learning on mobile devices in fact in this study the vast majority of students accessed the online videos at home on laptops or desktops However, in part, this is likely due to the nature of the taught subject, that being programming.
The research involved prerecording the lecture in smaller timed units and then uploading for distribution to counteract existing quality issues with recording entire live lectures. However the advancement and consequential improvement in quality of in situ lecture capture equipment may well help negate the need to record elsewhere. The research has also highlighted an area of potentially very significant use for performance analysis and improvement that could have major implications for the quality of teaching. A study of the analytics of the viewings of the videos could well provide a quick response formative feedback mechanism for the lecturer. If a videoed lecture either recorded live or later is a true reflection of the face to face lecture an analysis of the viewing patterns for the video may well reveal trends that correspond with the live delivery.

Video Lecture Capture : Student Engagement

Video Capture of university lectures enables learners to be more flexible in their learning behaviour, for instance choosing to attend lectures in person or watch later. However attendance at lectures has been linked to academic success and is of concern for faculty staff contemplating the introduction of Video Lecture Capture. This research study was devised to assess the impact on learning of recording lectures in computer programming courses. The study also considered behavioural trends and attitudes of the students watching recorded lectures, such as when, where, frequency, duration and viewing devices used. The findings suggest there is no detrimental effect on attendance at lectures with video materials being used to support continual and reinforced learning with most access occurring at assessment periods. The analysis of the viewing behaviours provides a rich and accessible data source that could be potentially leveraged to improve lecture quality and enhance lecturer and learning performance.

The use of YouTube Analytics of Video Lecture Capture as a Teaching and Learning Performance Enhancer

Do patterns in the YouTube viewing analytics of Lecture Capture videos point to areas of potential teaching and learning performance enhancement? The goal of this action based research project was to capture and quantitatively analyse the viewing behaviours and patterns of a series of video lecture captures across several computing modules in Queen’s University, Belfast, Northern Ireland. The research sought to establish if a quantitative analysis of viewing behaviours coupled with a qualitative evaluation of the material provided from the students could be correlated to provide generalised patterns that could then be used to understand the learning experience of students during face to face lectures and, thereby, present opportunities to reflectively enhance lecturer performance and the students’ overall learning experience and, ultimately, their level of academic attainment.

Using Digital Photography and Video in Participant Observation of Contentious Events

In this article, we discuss our experiences of using photography and video while observing contentious parades and protests in Belfast. We show how our use of these methods drew us into a series of unplanned for non-verbal interactions with other event participants who were also freely and abundantly using photographic and filming equipment to capture their own images. This interactive use of photography and video affected us emotionally and influenced what we noticed and what we omitted in our observations. In particular, it forced us to reflect upon and question our role as researchers in the events we observed and in the changing balance of power between researchers and researched.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
Project Source Code

Teaching Programming - Understanding Lecture Capture YouTube Analytics

ABSTRACT
The proliferation in the use of video lecture capture in universities worldwide presents an opportunity to analyse video watching patterns in an attempt to quantify and qualify how students engage and learn with the videos. It also presents an opportunity to investigate if there are similar student learning patterns during the equivalent physical lecture. The goal of this action based research project was to capture and quantitatively analyse the viewing behaviours and patterns of a series of video lecture captures across several university Java programming modules. It sought to study if a quantitative analysis of viewing behaviours of Lecture Capture videos coupled with a qualitative evaluation from the students and lecturers could be correlated to provide generalised patterns that could then be used to understand the learning experience of students during videos and potentially face to face lectures and, thereby, present opportunities to reflectively enhance lecturer performance and the students’ overall learning experience. The report establishes a baseline understanding of the analytics of videos of several commonly used pedagogical teaching methods used in the delivery of programming courses. It reflects on possible concurrences within live lecture delivery with the potential to inform and improve lecturing performance.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

Exploring the Views of Police Officers on the Use of Video Taped Evidence in Child Abuse Cases in Northern Ireland

This paper sets out to explore the views and attitudes of police officers in the Greater Belfast area, concerning the process and use of video taped interviews with child witnesses, subsequently used as court evidence in child abuse cases. The information was collected by means of a postal questionnaire, completed by police officers who had all experienced joint interviews with social workers of child witnesses. With the increased use of video evidence as an alternative to the distressing experience of a child appearing in court to give evidence, the research findings and conclusions provide clear messages about future developments both nationally and internationally.

A VLSI Architecture for Variable Block Size Video Motion Estimation

With the advent of new video standards such as MPEG-4 part-10 and H.264/H.26L, demands for advanced video coding, particularly in the area of variable block size video motion estimation (VBSME), are increasing. In this paper, we propose a new one-dimensional (1-D) very large-scale integration architecture for full-search VBSME (FSVBSME). The VBS sum of absolute differences (SAD) computation is performed by re-using the results of smaller sub-block computations. These are distributed and combined by incorporating a shuffling mechanism within each processing element. Whereas a conventional 1-D architecture can process only one motion vector (MV), this new architecture can process up to 41 MV sub-blocks (within a macroblock) in the same number of clock cycles.

Multi-state CDW approximation to electron capture during slow p-H collisions

The first complete multi-state CDW close coupling calculations which use a fully normalized basis set are performed. The results obtained at impact energies in the region of 10 keV for total and n = 2 capture cross sections are in reasonably good accord with experiment despite the fact that only the ground states of both species and the n = 2 states of the projectile are incorporated into the model. The theory has significant advantages over other atomic and molecular expansions which may require extensive bases to obtain similar accuracy.

Energy dependence for pair production with electron capture in relativistic heavy-ion collisions

In 'Charge transfer from the negative-energy continuum: alternative mechanism for pair production in relativistic atomic collisions', Eichler (1995 Phys. Rev. Lett. 75 3653) proposes an alternative mechanism for capture by pair production, and from it derives an analytic expression for the total cross section with a surprisingly strong energy dependence. We show that, in fact, there is no alternative mechanism; rather the above mechanism may be more transparently viewed as an ionization-like transition in one centre with inclusion of continuum distortion by the second centre. We further show that to Centre the initial and final states on the target and projectile leads to confusion in the momentum transfer vectors, and hence, respectively that the alleged high-energy behaviour is erroneous.