The international journal of learning 

About: The international journal of learning is an academic journal. The journal publishes majorly in the area(s): Higher education & Educational technology. It has an ISSN identifier of 1447-9540. Over the lifetime, 917 publications have been published receiving 6274 citations.

Affect-aware tutors: recognising and responding to student affect

Abstract: Theories and technologies are needed to understand and integrate the knowledge of student affect (e.g., frustration, motivation and self-confidence) into learning models. Our goals are to redress the cognitive versus affective imbalance in teaching systems, develop tools that model student affect and build tutors that elicit, measure and respond to student affect. This article describes our broad approach towards this goal and our three main objectives: develop tools for affect recognition, interventions in response to student affect, and emotionally animated agents.

Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model

Abstract: This article argues that there is a need for Personal Recommender Systems (PRSs) in Learning Networks (LNs) in order to provide learners with advice on the suitable learning activities to follow. LNs target lifelong learners in any learning situation, at all educational levels and in all national contexts. They are community-driven because every member is able to contribute to the learning material. Existing Recommender Systems (RS) and recommendation techniques used for consumer products and other contexts are assessed on their suitability for providing navigational support in an LN. The similarities and differences are translated into specific requirements for learning and specific requirements for recommendation techniques. The article focuses on the use of memory-based recommendation techniques, which calculate recommendations based on the current data set. We propose a combination of memory-based recommendation techniques that appear suitable to realise personalised recommendation on learning activities in the context of e-learning. An initial model for the design of such systems in LNs and a roadmap for their further development are presented.

The Web 2.0 way of learning with technologies

Abstract: While there is a lot of hype around various concepts associated with the term Web 2.0 in industry, little academic research has so far been conducted on the implications of this new approach for the domain of education. Much of what goes by the name of Web 2.0 can, in fact, be regarded as new kinds of learning technologies, and can be utilised as such. This paper explains the background of Web 2.0, investigates the implications for knowledge transfer in general, and then discusses its particular use in eLearning contexts with the help of short scenarios. The main challenge in the future will be to maintain essential Web 2.0 attributes, such as trust, openness, voluntariness and self-organisation, when applying Web 2.0 tools in institutional contexts.

Towards a task model for mobile learning: a dialectical approach

Abstract: Our approach to understanding mobile learning begins by describing a dialectical approach to the development and presentation of a task model using the socio-cognitive engineering design method This analysis synthesises relevant theoretical approaches We then examine two field studies, which feed into the development of the task model

How do you know they are learning? The importance of alignment in higher education

Abstract: The success of any learning environment is determined by the degree to which there is adequate alignment among eight critical factors: 1) goals, 2) content, 3) instructional design, 4) learner tasks, 5) instructor roles, 6) student roles, 7) technological affordances, and 8) assessment. Evaluations of traditional, online, and blended approaches to higher education teaching indicate that the most commonly misaligned factor is assessment. Simply put, instructors may have lofty goals, high-quality content, and even advanced instructional designs, but most instructors tend to focus their assessment strategies on what is easy to measure rather than on what is important. Adequate assessment should encompass all four learning domains: cognitive, affective, conative, and psychomotor. This paper describes procedures for the development and use of reliable and valid assessments in higher education.