Perceptions of online tutorials for distance learning in mathematics and computing

We report on student and staff perceptions of synchronous online teaching and learning sessions in mathematics and computing. The study is based on two surveys of students and tutors conducted 5 years apart, and focusses on the educational experience as well as societal and accessibility dimensions. Key conclusions are that both staff and students value online sessions, to supplement face-to-face sessions, mainly for their convenience, but interaction within the sessions is limited. Students find the recording of sessions particularly helpful in their studies.

The three people you need for distance learning

Presentation at M25 Learning Technology Group, FutureLearn, 15 November 2017

Learning analytics from distance learning

Presentation at M25 Learning Technology Group, FutureLearn, 15 November 2017

Operational issues and plans for distance learning at UCL

Presentation at M25 Learning Technology Group, FutureLearn, 15 November 2017

Some aspects of grading Java code submissions in MOOCs

Recently, massive open online courses (MOOCs) have been offering a new online approach in the field of distance learning and online education. A typical MOOC course consists of video lectures, reading material and easily accessible tests for students. For a computer programming course, it is important to provide interactive, dynamic, online coding exercises and more complex programming assignments for learners. It is expedient for the students to receive prompt feedback on their coding submissions. Although MOOC automated programme evaluation subsystem is capable of assessing source programme files that are in learning management systems, in MOOC systems there is a grader that is responsible for evaluating students’ assignments with the result that course staff would be required to assess thousands of programmes submitted by the participants of the course without the benefit of an automatic grader. This paper presents a new concept for grading programming submissions of students and improved techniques based on the Java unit testing framework that enables automatic grading of code chunks. Some examples are also given such as the creation of unique exercises by dynamically generating the parameters of the assignment in a MOOC programming course combined with the kind of coding style recognition to teach coding standards.

Development of an institutional framework to guide transitions into enhanced blended learning in higher education

The rapidly changing digital landscape is having a significant influence on learning and teaching. Our study assesses the response of one higher education institution (HEI) to the changing digital landscape and its transition into enhanced blended learning, which seeks to go beyond the early implementation stage to make the most effective use of online learning technologies to enhance the student experience and student learning outcomes. Evidence from a qualitative study comprising 20 semi-structured interviews, informed by a literature review, has resulted in the development of a holistic framework to guide HEIs transitioning into enhanced blended learning. The proposed framework addresses questions relating to the why (change agents), what (institutional considerations), how (organisational preparedness) and who (stakeholders) of transitions into enhanced blended learning. The involvement of all stakeholder groups is essential to a successful institutional transition into enhanced blended learning.

Shaping the future of learning using the student voice: we’re listening but are we hearing clearly?

Student voice data is a key factor as Manchester Metropolitan University strives to continually improve institutional technology enhanced learning (TEL) infrastructure. A bi-annual Institutional Student Survey enables students to communicate their experience of learning, teaching and assessment on programmes and specific units studied. Each cycle of the survey contains approximately 40–50,000 free text comments from students pertaining to what they appreciate and what they would like to see improved. A detailed thematic analysis of this data has identified 18 themes, arranged into six categories relating to the ‘Best’ aspects of courses, and 25 themes, arranged in seven categories in relation to aspects of courses considered to be ‘in need of improvement’. This student data was then used as a basis for semi-structured interviews with staff. Anecdotally, evidence suggested that student expectations and staff expectations around TEL and the virtual learning environment (VLE) differed. On-going evaluation of this work has highlighted a disconnect. In significant instances, academic colleagues seemingly misinterpret the student voice analysis and consequently struggle to respond effectively. In response to the analysis, the learning technologist's role has been to re-interpret the analysis and redevelop TEL staff development and training activities. The changes implemented have focused on: contextualising resources in VLE; making lectures more interactive; enriching the curriculum with audio–visual resources; and setting expectations around communications.

Engaging distance learners

Presentation at M25 Learning Technology Group, FutureLearn, 15 November 2017

Portfolios for learning; course design and platform choices

Presentation at M25 Learning Technology Group, FutureLearn, 15 November 2017