Affective E Learning Model for Recognising Learner Emotions

Online learning is commonly accepted as a support tool for educators as well as a medium of delivery of any-time, any-where content of a wide range of study programs to a widely dispersed learner community. Web-based learning environments are a relatively new medium of learning to Sri Lankan universities. A research was carried out by T. C. Sandanayake, A. P. Madurapperuma, and D. Dias in order to find a prospective solution and develop an Affective E Learning Model for Recognising Learner Emotions.

Emotions are important in adult learning because they can  either impede or motivate learning. Electronic learning has  been portrayed as less emotional and more impersonal or as  lacking in emotional richness when compared to face-to-face  learning since the learner is physically invisible to the teacher. Modern education system uses multiple methods and tools  such as electronic learning, mobile learning, problem based  learning, project based activities, online discussion groups and chat forums to facilitate learning. . One of the major problems in distance learning is the lack of methods to recognise learner behavior.

Online education programs have enabled learning  opportunities to learners that allow for breaking away from  space and time constraints. In Sri Lankan context this problem becomes worse since the online delivery mode is quite new for the higher educational system.   The aim of the research study wasto build a model to recognize the e learner’s emotional state with respect to their learning performances.  The proposed e learning model addresses the issue of not recognizing and responding to e learner’s emotions while they learn.  This model will also be helpful to identify the e learners’ learning performances while measuring the emotional state.  The research study has been designed aiming the undergraduate learners following an honours degree in Bachelor of Science in IT, University of Moratuwa.   The high level architecture of the proposed system describes the connectivity of the existing online environment and the novel approach of online learning which enables affect recognition.  Current study explores the learner behavior using Barry Kort’s Learning Spiral Model.  This article proffers a novel model by which to conceptualize the impact of emotions upon learning with the application of Barry Kort’s learning spiral model. This model is described by two major constructs which are the learning level of individual learner and the emotional state of the learner. The research study measures both the elements individually and separately. When measuring the learning level of the learner, the study will be using six observable parameters of online learner. Multiple regression analysis will be used in measuring the level of learners.

 The emotional element of the leaner will be measured using multidimensional self reported instrument which assesses online learner’s individual emotional reactions in achievement situations. The tool is termed as Achievement Emotion Questionnaire for Online Learning and four positive emotions and five negative emotions are measured in the real time online learning environment. The AEQ for online learning is scored in five point Likert scale and items included in the questionnaire were based on learner’s emotional experiences experimented by Rainhard Pekrun. The questions are categorised in to six different sections in online learning and assesses the emotional state of the learner. Finally the learner’s emotional state and the level of learning is mapped in two dimensional space and the responses are used to enhance leaner performances.


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