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.

The Effect of Seat Location in Lecture Theatres on Academic Performance

The purpose of this research study was to investigate and identify possible patterns relating to academic performance on the effects of university students self-selecting where to sit in a lecture theatre.
The key research questions are:
1. Does seating position affect student performance?
2. Do the most academically able and engaged students regularly sit at the front of lecture theatres?
Academic achievement
Preliminary results suggest significant assessment score differences between those that sit at the front and those that sit further the back. Of those that received a grade of 75%+ (Grade A) 6.67% regularly sat at the back. With the same group 46.67% regularly sat at the front. Of the group that scored less than 50% (Grade D) 0% of students regularly sat at the front. 12.50% regularly sat in the middle zones with 37.50% sitting at the back. It was also observed that the remaining numbers did not consistently sit in the same zone.

Temporal movement
There is little evidence of movement between seating zones of the Grade A group throughout the 24 week period. However there was considerable movement with the Grade D group. Although still under analysis there appears be a pattern of students in this group graduating towards the back seating positions over the course of the programme.

Engagement
The frequency of completed entries on PinPoint was also used as an indicator of engagement. With the Grade A group 75% of them regularly completed an entry whereas in the Grade D group this drops to less than 50%.
Further analysis on the attitudinal factors in relational to seating position and performance are ongoing, but preliminary results suggest that those students that scored highly in attitude tended to sit at the front and middle sections.
It would indeed appear that the more highly engaged and academically capable students voluntarily sit at the front for most lectures. Interestingly as the course progresses those who had lesser engagement and below average midterm results tend to began to sit progressively toward the back. If this is a repeatable pattern then a linear regression analysis of the seating positions and midterm results could help predict students in danger of failing.

Extending BPM Environments of Your Choice with Performance Related Decision Support

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools process optimizations or a combination Of Such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

Uncertainty profiles are used to study the effects of contention within cloud and service-based environments. An uncertainty profile provides a qualitative description of an environment whose quality of service (QoS) may fluctuate unpredictably. Uncertain environments are modelled by strategic games with two agents; a daemon is used to represent overload and high resource contention; an angel is used to represent an idealised resource allocation situation with no underlying contention. Assessments of uncertainty profiles are useful in two ways: firstly, they provide a broad understanding of how environmental stress can effect an application’s performance (and reliability); secondly, they allow the effects of introducing redundancy into a computation to be assessed

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.

iLectures - Exploring the interactive lecture using web-based broadcasting technology

The continued use of traditional lecturing across Higher Education as the main teaching and learning approach in many disciplines must be challenged. An increasing number of studies suggest that this approach, compared to more active learning methods, is the least effective. In counterargument, the use of traditional lectures are often justified as necessary given a large student population. By analysing the implementation of a web based broadcasting approach which replaced the traditional lecture within a programming-based module, and thereby removed the student population rationale, it was hoped that the student learning experience would become more active and ultimately enhance learning on the module. The implemented model replaces the traditional approach of students attending an on-campus lecture theatre with a web-based live broadcast approach that focuses on students being active learners rather than passive recipients. Students ‘attend’ by viewing a live broadcast of the lecturer, presented as a talking head, and the lecturer’s desktop, via a web browser. Video and audio communication is primarily from tutor to students, with text-based comments used to provide communication from students to tutor. This approach promotes active learning by allowing student to perform activities on their own computer rather than the passive viewing and listening common encountered in large lecture classes. By analysing this approach over two years (n = 234 students) results indicate that 89.6% of students rated the approach as offering a highly positive learning experience. Comparing student performance across three academic years also indicates a positive change. A small data analytic analysis was conducted into student participation levels and suggests that the student cohort's willingness to engage with the broadcast lectures material is high.

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.