Scoping a vision for formative e-assessment: a project report for JISC

Assessment is an integral part of teaching and learning. If the relationship between teaching and learning were causal, i. e. if students always mastered the intended learning outcomes of a particular sequence of instruction, assessment would be superfluous. Experience and research suggest this is not the case: what is learnt can often be quite different from what is taught. Formative assessment is motivated by a concern with the elicitation of relevant information about student understanding and / or achievement, its interpretation and an exploration of how it can lead to actions that result in better learning. In the context of a policy drive towards technology-enhanced approaches to teaching and learning, the question of the role of digital technologies is key and it is the latter on which this project particularly focuses. The project and its deliverables have been informed by recent and relevant literature, in particular recent work by Black andIn this work, they put forward a framework which suggests that assessment for learning their term for formative assessment can be conceptualised as consisting of a number of aspects and five keystrategies. The key aspects revolve around the where the learner is going, where the learner is right now and how she can get there and examines the role played by the teacher, peers and the learner. Language: English Keywords: assessments, case studies, design patterns, e-assessmen

Computer assisted formative assessment: supporting students to become more reflective learners

e-Assessment is being advocated in the UK as our way of introducing a more personalised learning agenda throughout the Higher Education sector. This paper discusses the findings from two projects where formative e-assessment has contributed to students taking more control of their own learning. One study set out to provide further insights into the role of electronic formative assessment and to point the way forward to new assessment practices, capitalising on a range of open source tools. The guiding vision was to pilot a series of formative assessments which have the potential to help shape learners as independent thinkers, making their own judgements and decisions about their learning in partnership with their peers and tutors. Other work consisted of evaluating a series of formative assessments given to Philosophy students. Lessons have been learned about the type of feedback that instructors and students think will be most useful and how using theis type of application promotes self reflection. The research reported here starts to illustrate how technology can be adapted to become more 'fit for pedagogical purpose?. The feedback offered by these systems encourages learner metacognition and aims to empower students to reflect and become independent thinkers. This approach sits well within a constructivist paradigm which has often been less well served in the past through formal summative assessment which is not an integral part of the knowledge construction process

Student profiling in a dispositional learning analytics application using formative assessment

How learning disposition data can help us translating learning feedback from a learning analytics application into actionable learning interventions, is the main focus of this empirical study. It extends previous work where the focus was on deriving timely prediction models in a data rich context, encompassing trace data from learning management systems, formative assessment data, e-tutorial trace data as well as learning dispositions. In this same educational context, the current study investigates how the application of cluster analysis based on e-tutorial trace data allows student profiling into different at-risk groups, and how these at-risk groups can be characterized with the help of learning disposition data. It is our conjecture that establishing a chain of antecedent-consequence relationships starting from learning disposition, through student activity in e-tutorials and formative assessment performance, to course performance, adds a crucial dimension to current learning analytics studies: that of profiling students with descriptors that easily lend themselves to the design of educational interventions

Beyond lecture capture: Student-generated podcasts in teacher education.

Podcasting in higher education most often takes the form of lecture capture or "coursecasting" as instructors record and disseminate lectures (King & Gura, 2007, p. 181). Studies published within the past five years continue to prioritise podcasting of lectures for the student audience, and to test the effectiveness of such podcasts via traditional pencil and paper assessments covering the material delivered via podcast (Hodges, Stackpole-Hodges, & Cox, 2008). A premise of this article is that in order to enhance learning outcomes via podcasting, it is necessary to move beyond coursecasting, toward podcasting with and by students, and to value key competencies and dispositions as learning outcomes. This article reports on a pilot study undertaken with teacher education students in an online ICT class, where students investigated podcasting and created reflective podcasts. The pilot study aimed to engage students actively in generating podcasts, incorporating a wider view of assessment and learning outcomes. Student-generated podcasts were self-assessed, and shared online in order to invite formative feedback from peers. A range of positive outcomes are reported, whereby students learned about and through podcasting, engaging in reflection, problem solving and interactive formative assessment

What learning analytics based prediction models tell us about feedback preferences of students

Learning analytics (LA) seeks to enhance learning processes through systematic measurements of learning related data and to provide informative feedback to learners and educators (Siemens & Long, 2011). This study examined the use of preferred feedback modes in students by using a dispositional learning analytics framework, combining learning disposition data with data extracted from digital systems. We analyzed the use of feedback of 1062 students taking an introductory mathematics and statistics course, enhanced with digital tools. Our findings indicated that compared with hints, fully worked-out solutions demonstrated a stronger effect on academic performance and acted as a better mediator between learning dispositions and academic performance. This study demonstrated how e-learners and their data can be effectively re-deployed to provide meaningful insights to both educators and learners

Accelerating the assessment agenda: thinking outside the black box

Over the last 10 years, learning and teaching in higher education have benefited from advances in social constructivist and situated learning research (Laurillard, 1993). In contrast, assessment has remained largely transmission orientated in both conception and in practice (see Knight & Yorke, 2003). This paper examines a number of recent developments, which exhibit innovation in electronic assessment developed at the UK's Open University. This paper argues for the development of new forms of e-assessment where the main driver is that of sound pedagogy rather than state of the art technological know-how and where open source products can move the field forward

Harnessing Technology: new modes of technology-enhanced learning: opportunities and challenges

A report commissioned by Becta to explore the potential impact on education, staff and learners of new modes of technology enhanced learning, envisaged as becoming available in subsequent years. A generative framework, developed by the researchers is described, which was used as an analytical tool to relate the possibilities of the technology described to learning and teaching activities. This report is part of the curriculum and pedagogy strand of Becta's programme of managed research in support of the development of Harnessing Technology: Next Generation Learning 2008-14. A system-wide strategy for technology in education and skills. Between April 2008 and March 2009, the project carried out research, in three iterative phases, into the future of learning with technology. The research has drawn from, and aims to inform, all UK education sectors