Exploring the Potential of Speech Recognition to Support Problem Solving and Reflection

Lecture Notes in Computer Science

Hansen

et al. 2015

Self Cite

Abstract. This paper reports on our progress on a systematic approach to operationalizing support in Fractions Lab -an exploratory learning environment for learning fractions in primary education. In particular, we focus on the question of what feedback to provide and consider in detail the implementation of feedback according to two dimensions: the purpose of the feedback, depending on the task-specific needs of the student, and the level of feedback, depending on the cognitive needs of the student. We present early findings from our design-based research that includes Wizard-of-Oz studies of the intelligent feedback system and student perception questionnaires.

Section: Purpose Of Feedbackmentioning

confidence: 99%

Section: Fractions Labmentioning

confidence: 99%

Purpose and Level of Feedback in an Exploratory Learning Environment for Fractions

Lecture Notes in Computer Science

Hansen

et al. 2015

Self Cite

“…The decision about what type of feedback to provide was based on a script. For more information, the reader is referred to Mavrikis et al (2014).…”

Section: -Instructive Feedback This Feedback Provided Detailed Instrmentioning

confidence: 99%

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

Grawemeyer

User Model User-Adap Inter

et al. 2017

Self Cite

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' a↵ective 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' a↵ective 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-a↵ect condition). Our results suggest that a↵ect-aware support contributes to reducing boredom and o↵-task behavior, and may have an e↵ect 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 a↵ect-aware modelling plays in the adaptive delivery of formative feedback to support learning.

“…Each session lasted on average 20 minutes. More information about the set up of the study can be found in Mavrikis et al [10].…”

Section: The Wizard-of-oz Studymentioning

confidence: 99%

“…We explored these particular types of feedback because the literature suggests they support students in their learning and because they fit our context [10].…”

Section: The Wizard-of-oz Studymentioning

confidence: 99%

Affect Matters: Exploring the Impact of Feedback During Mathematical Tasks in an Exploratory Environment

Grawemeyer

Lecture Notes in Computer Science

et al. 2015

Self Cite

Abstract. 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.