Affective learning: improving engagement and enhancing learning with affect-aware feedback

This paper describes the design and ecologically valid evaluation of a learner model that lies at the heart of an intelligent learning environment called iTalk2Learn. A core objective of the learner model is to adapt formative feedback based on students’ affective states. Types of adaptation include what type of formative feedback should be provided and how it should be presented. Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process. This paper reports results from a quasi-experimental evaluation, in authentic classroom settings, which compared a version of iTalk2Learn that adapted feedback based on students’ affective states as they were talking aloud with the system (the affect condition) with one that provided feedback based only on the students’ performance (the non-affect condition). Our results suggest that affect-aware support contributes to reducing boredom and off-task behavior, and may have an effect on learning. We discuss the internal and ecological validity of the study, in light of pedagogical considerations that informed the design of the two conditions. Overall, the results of the study have implications both for the design of educational technology and for classroom approaches to teaching, because they highlight the important role that affect-aware modelling plays in the adaptive delivery of formative feedback to support learning

The impact of affect-aware support on learning tasks that differ in their cognitive demands

This paper investigates the effect of affect-aware support on learning tasks that differ in their cognitive demands. We conducted a study with the iTalk2learn platform where students are undertaking fractions tasks of varying difficulty and assigned in one of two groups; one group used the iTalk2learn platform that included the affect-aware support, whereas in the other group the affect-aware support was switched off and support was provided based on students’ performance only. We investigated the hypothesis that affect-aware support has a more pronounced effect when the cognitive demands of the tasks are higher. The results suggest that students that undertook the more challenging tasks were significantly more in-flow and less confused in the group where affect-aware support was provided than students who were supported based on their performance only

Design and evaluation of adaptive feedback to foster ICT information processing skills in young adults

This paper explores the provision of adaptive hints based on attainment levels in the context of supporting the development of young adults' ICT information processing skills. We describe the design of the LIBE VLE, particularly its personalisation and adaptation features, and a User Study undertaken with young adults at a vocational education centre. Using data collected through the LIBE VLE, we analyse the relationships between learners' accessing of hints, motivation, and performance. Results point to a positive effect of accessing of hints on students' perception of the LIBE VLE and their likelihood of using it again for further learning; and also a positive effect of students' interest in the course subject on their engagement and performance in course activities. These findings have important implications for supporting young adults in developing key competences necessary for integration into the workforce and for fostering self-regulated lifelong learning

Affect matters: exploring the impact of feedback during mathematical tasks in an exploratory environment

We describe a Wizard-of-Oz study that investigates the impact of different types of feedback on students’ affective states. Our results indicate the importance of matching carefully the affective state with appropriate feedback in order to help students transition into more positive states. For example when students were confused affect boosts and specific instruction seem to be effective in helping students to be in flow again. We discuss this and other effective ways to and implications for the development of our system and the field in general

The impact of feedback on students’ affective states

Affective states play a significant role in students' learning behaviour. Positive affective states can enhance learning, while negative affective states can inhibit it. This paper describes a Wizard-of-Oz study that investigates the impact of different types of feedback on students' affective states. Our results indicate the importance of providing feedback matched carefully to the affective state of the students in order to help them transition into more positive states. For example when students were confused affect boosts and specific instructive feedback seem to be effective in helping students to be in flow again. We discuss this and other ways to adapt the feedback, together with implications for the development of our system and the field in general

Using graph-based modelling to explore changes in students’ affective states during exploratory learning tasks

We describe a graph-based modelling approach to exploring interactions associated with a change in students' affective state when they are working with an exploratory learning environment (ELE). Student-system interactions data collected during a user study was modelled, visualized and queried as a graph. Our findings provide new insights into how students are interacting with the ELE and the effects of the system's interventions on students' affective states

Using graph-based modelling to explore changes in students’ affective states during exploratory learning tasks

This paper describes how graph-based modelling can be used to explore interactions associated with a change in students' affective state when they are working with an exploratory learning environment (ELE). We report on a user study with an ELE that is able to detect students' affective states from their interactions and speech. The data collected during the user study was modelled, visualized and queried as a graph. We were interested in exploring if there was a difference between low- and high-performing students in the kinds of interactions that occurred during a change in their affective state. Our findings provide new insights into how students are interacting with the ELE and the effects of the system's interventions on students' affective states

Light-bulb moment?: towards adaptive presentation of feedback based on students' affective state

Affective states play a significant role in students’ learning behaviour. Positive affective states can enhance learning, whilst negative affective states can inhibit it. This paper describes a Wizard-of-Oz study which investigates whether the way feedback is presented should change according to the affective state of a student, in order to encourage affect change if that state is negative. We presented high-interruptive feedback in the form of pop-up windows in which messages were immediately viewable; or low-interruptive feedback, a glow- ing light bulb which students needed to click in order to access the messages. Our results show that when students are confused or frustrated high-interruptive feedback is more effective, but when students are enjoying their activity, there is no difference. Based on the results, we present guidelines for adaptively tailoring the presentation of feedback based on students’ affective states when interacting with learning environments