Emotions, Technology, and Learning

Sharon Y. Tettegah, Michael P. McCreery

• Publisher: Academic Press
• Year: 2015
• ISBN:
  9780128007143
• Topic: Psychology
• Subtopic: Cognitive Psychology & Cognition
• Index: Psychology

Research suggests two important roles of emotion related to learning and technology. First, emotion can be the key factor that is being learned or taught through technological means. Second, emotional responses with and through technology can alter what is being learned or how the content is learned. The goal of this volume is to compile and synthesize research that addresses these two perspectives by focusing on the relationship between emotion and learning as facilitated by technology. The book is divided into four sections to represent the specific interest related to emotion and learning: Theory and Overview of Emotions and Learning; Emotions and Learning Online; Technology for Emotional Pedagogy with Students; and Technology of Emotional Pedagogy with Teachers.

• Provides a deeper theoretical and empirical perspective of emotion and learning
• Discusses how blended and online learning impact our ability to share emotion or learn emotion
• Explores how students learn emotion, share emotion, and how it impacts their ability to learn
• Examines how teachers learn emotion, share, emotion, and how it impacts their ability to teach through technology
• Addresses student diversity

Section II

Technology, Emotions, and Classroom Use

Chapter 5

Using Errors to Enhance Learning Feedback in Computer Programming

Man-Wai Chu; Jacqueline P. Leighton University of Alberta, Edmonton, AB, Canada

Abstract

The results of a quasi-experimental study, which involved an instructional intervention based upon the Learning Errors and Formative Feedback (LEAFF) model in a technology-rich learning environment, are reported. The instructional intervention involved an explicit discussion about the pedagogical value of errors with undergraduate students completing a computer-programming class. Three specific research questions guided the study: (1) Does an instructional intervention based upon the LEAFF model have an effect on students’ feelings of well-being as they learn computer programming? (2) Does an instructional intervention based upon the LEAFF model have an effect on the number of errors students report? And (3) Does an instructional intervention based upon the LEAFF model have an effect on students’ preference of feedback delivery and use? The instructional intervention was associated with statistically significant effects on students’ sense of well-being in the learning environment, production of errors for formative purposes, and reported use of feedback.

Keywords

Learning Errors and Formative Feedback model

Technology-rich environment

Computer programming class

Acknowledgement

Preparation of this chapter was supported by a grant to the second author from the Social Sciences and Humanities Research Council of Canada (SSHRC Grant No. 410-2011-0811). Grantees undertaking such projects are encouraged to express freely their professional judgment. This paper, therefore, does not necessarily represent the positions or the policies of the Canadian government, and no official endorsement should be inferred. Correspondence pertaining to this chapter should be directed to Man-Wai Chu or Jacqueline P. Leighton by airmail at 6-110 Education North, Centre for Research in Applied Measurement and Evaluation (CRAME), Dept. of Educational Psychology, Faculty of Education, University of Alberta, Edmonton, Alberta, CANADA T6G 2G5 or email at [email protected] or [email protected].

Learning is not only a cognitive, but also a highly social and emotional process (Damasio, 2001). To facilitate the experience of learning for students as well as the successful acquisition of knowledge and skills, instructors should understand how human emotions and social interactions enhance or hinder learning, and use this information to build learning environments accordingly (Lajoie, 2008). Creating learning environments that are experienced by students as emotionally safe could facilitate their sense of ease when experimenting with ideas, making errors as they learn, and interpreting feedback meaningfully to correct errors without fear of looking silly or feeling unintelligent (Leighton, Chu, & Seitz, 2013; see also Bustos Gomez & Leighton, 2013). In meeting the goal of building learning environments that are sensitive to the emotions and social interactions of students, technology may be a powerful ally. For example, technology can facilitate the anonymous expression of ideas via online posts, and permit constructive and respectful feedback to be crafted in response to ideas (Roed, 2003). Although we were unable to find empirical research articles focused specifically on using technology to increase students’ perceptions of safety in the classroom (however, see Roed, 2003), we expect that just as technology has facilitated the instruction of diverse learners (e.g., assistive technology for learning disabilities; see Lewis, 1998), it could also facilitate instructional interventions such as feedback delivery to create emotionally safe learning environments for students; however, this remains an empirical question.

Although the content and delivery of feedback has been investigated previously (e.g., Bangert-Drowns, Kulik, Kulik, & Morgan, 1991; Kluger & DeNisi, 1996, for a historical review and meta-analysis; Shute, 2008), one issue that remains relatively unexplored is student preferences over the mode in which feedback is delivered following assessment activities. Surprisingly, not much research has focused on learners’ emotional responses to feedback (Shute, 2008). A recent learning model attempts to address the complex relationship between feedback and students’ emotional responses. The model, called the Learning Errors and Formative Feedback (LEAFF), focuses on students’ mental models of their learning environment, including assessment activities (Leighton et al., 2013). One reason to investigate student preferences over the mode in which feedback is delivered rests with increasing the likelihood that students (1) experience productive emotional responses in relation to feedback; (2) acknowledge and accept the feedback given; and (3) use it to modify their learning in constructive ways. The objective of this chapter is to investigate the effects of an instructional intervention based upon the LEAFF model within a technology-rich learning environment. More specifically, the research questions guiding this study include: (1) Does an intervention based upon the LEAFF model have an effect on students’ feelings of well-being as they learn computer programming? (2) Does an intervention based upon the LEAFF model have an effect on the number of errors students report? And (3) Does an intervention based upon the LEAFF model have an effect on students’ preference of feedback delivery and use? The chapter is divided into four sections. We begin with a description of the LEAFF model, followed by the method and procedures of the quasi-experimental study we conducted to test aspects of the LEAFF model, along with the results. In the final section, we summarize and discuss the findings and conclude with the implications of this work.

LEAFF Model

The LEAFF model (Leighton et al., 2013), shown in Figure 5.1, involves three parts. The first part focuses on the instructional climate within classrooms, where instructors engage in pedagogical behaviors that either explicitly or implicitly promote safety or risk for learners experimenting with new knowledge and skills. Behaviors that explicitly promote safety might include verbal expressions about showing respect for others’ views; for example, a teacher might say “we must be considerate of each other’s values and opinions during the discussion today.” Behaviors that implicitly promote safety might include showing patience in body language (e.g., not tapping a finger or making facial expressions to indicate urgency) when a student is struggling to understand a concept.

Figure 5.1 The learning errors and formative feedback (LEAFF) model (Leighton et al., 2013).

One approach that is hypothesized to facilitate the creation of a safe learning environment is to explicitly discuss the value of “learning” errors with students. Learning errors are made in the formative stages of acquiring new knowledge and skills. Learning errors (from here on, simply called errors) signal student misunderstandings and can be used constructively to enhance future learning. Instructors are encouraged to discuss and help students understand that errors are a natural and necessary part of learning. It is expected that over time and with continued discussion of the value of errors, students may come to experience greater mastery-learning orientations, where errors are viewed as opportunities for clarification and pathways to deeper understanding. Further, students may come to experience increasingly positive emotions in learning environments where errors are viewed as opportunities for growth—a sense that the stakes are lower when errors are made during the learning process because they are viewed as a necessary part of learning complex skills. The explicit discussion of errors is designed to challenge students’ assumptions about how innate intelligence limits learning potential and, instead, encourage a “growth” mindset (Dweck, 2006).

The second part of the LEAFF model focuses on students’ mental models of the emotional (affective) and cognitive components of the classroom environment. Mental models (Johnson-Laird, 1983) are internal representations that reflect an individual’s perception and understanding of the world around him or her for the purposes of reasoning and problem solving. Mental models contain information, as perceived by the individual...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Foreword
• Preface
• Section I: Emotions and Learning in Online Environments
• Section II: Technology, Emotions, and Classroom Use
• Section III: Exploring Affect With and Through Technology: Research and Practice
• Index