John M. Keller

Development and use of the ARCS model of instructional design

The ARCS Model of motivation was developed in response to a desire to find more effective ways of understanding the major influences on the motivation to learn, and for systematic ways of identifying and solving problems with learning motivation. The resulting model contains a four category synthesis of variables that encompasses most of the areas of research on human motivation, and a motivational design process that is compatible with typical instructional design models. Following its development, the ARCS Model was field tested in two inservice teacher education programs. Based on the results of these field tests, the ARCS Model appears to provide useful assistance to designers and teachers, and warrants more controlled studies of its critical attributes and areas of effectiveness.

Learner Motivation and E-Learning Design: A Multinationally Validated Process.

A general model for motivational design of instruction is described and reviewed in terms of its application to E-learning contexts. Following a description of what is meant by E-learning environments and an overview of the four category model and design process known as the ARCS model, a variety of studies are summarized. The ARCS model is based on a synthesis of motivational concepts and a problem-solving approach to design, rather than the application of specific motivational solutions that are advocated without regard to the specific characteristics of a given situation. The first group of reviewed studies illustrates the results of testing the motivational design process in several different E-learning settings, in relation to learner self-regulation and in terms of the interaction of personality characteristics and motivational strategies. The second group of studies includes tests of the validity of a simplified motivational design process that has been used in diverse types of E-learning settings, including multiple countries and cultures. Overall, the results of these empirical studies have confirmed the validity of this model for the systematic design of motivationally enhanced instruction in E-learning settings with regard to lowering drop-out rates and other positive motivational outcomes.

Motivation and instructional design: A theoretical perspective

We have not given adequate systematic attention to the problem of motivation in instructional theory and technology, to the understanding of motivation in individual learners, or to the development of a technology for influencing motivation (Cooley & Lohnes, 1976; Cronbach & Snow, 1976). We know, as a rule of thumb, that we should introduce novelty, uncertainty, or a sense of mystery at the beginning of a program to elicit attention and, it is hoped, enthusiasm, and we know that we should use reinforcement to help sustain desirable changes in behavior, but neither of these principles constitutes an adequate understanding of motivation. The purpose of this paper is to present a theoretical approach to understanding motivation in relation to other factors that influence learning and the design of instruction. In this context, several illustrative research studies are reviewed along with an introduction to a systematic process of influencing motivation. This presentation is not exhaustive, but serves as an introduction to the approach, and as a basis for subsequent elaborations of the issues and tech-

First principles of motivation to learn and e 3 -learning

Technology‐assisted learning systems are being developed at ever increasing rates, and the labels applied to such systems are growing with them. For example, not only do we have e‐learning, but we also have hybrid learning, online learning, and mobile learning (m‐learning), to mention only a few. Considering that technology is being incorporated in virtually all courses, this article uses the single term e3‐learning, as introduced by Spector and Merrill in this special issue to refer to these systems collectively with the emphasis on effectiveness, efficiency, and engagement. Learning concerns learner motivation. Five first principles of motivation and volition that characterize learning systems that effectively motivate students are introduced in this article.

Effectiveness of Motivationally Adaptive Computer-Assisted Instruction on the Dynamic Aspects of Motivation

The purpose of this study was to examine the effects of a prototype of motivationally-adaptive computer-assisted instruction (CAI). The foundation for motivational theory and design was provided by the ARCS model (an acronym formed from attention, relevance, confidence, and satisfaction). This model provides a definition of motivation, a motivational design process, and recommendations for motivational strategies. Three treatment conditions were considered: (a) motivationally adaptive CAI, (b) motivationally saturated CAI, and (c) motivationally minimized CAI. Dependent variables were effectiveness, perceived motivation (both overall motivation and each of A, R, C, & S components), efficiency, and continuing motivation. The motivationally adaptive CAI showed higher effectiveness, overall motivation, and attention than the other two CAI types. For efficiency, both motivationally adaptive CAI and motivationally minimized CAI were higher than motivationally saturated CAI. For continuing motivation, there were no significant differences among the three CAI types, but a significant correlation was found between overall motivation and continuing motivation across the three CAI types. This study supports the conclusion that CAI can be designed to be motivationally adaptive to respond to changes in learner motivation that may occur over time. It also illustrates that the ARCS model can be useful and effective in support of designing for these dynamic aspects of motivation.

Effects of Motivational and Volitional Email Messages (MVEM) with Personal Messages on Undergraduate Students' Motivation, Study Habits and Achievement.

This study investigated what kind of supportive information can be effective in improving the situation where there were severe motivational challenges. Motivational and volitional email messages (MVEM) were constructed based on an integrated model of four theories and methods, which are Kellers ARCS model, Kuhls action control theory, Gollwitzers Rubicon model of motivation and volition, and Visser & Kellers strategy of motivational messages, and distributed with personal messages created based on audience analysis to a large undergraduate class. In order to examine the effects of the messages on motivation for the course, study habits (study time), and achievement (test grade), MVEM were sent to 30 students (Personal Message Group: PMG) with personal messages and to 71 students (Non-Personal Message Group: NonPMG) without personal messages. Results indicated that PMG showed a higher level of motivation, especially in regard to confidence, than NonPMG. Also, the mean test grade of PMG increased so that the initial difference of the test grade between the two groups significantly decreased. Although there was no difference between the two groups in study habits, the findings suggest that personal messages addressing specific individual problems raise the positive effects of MVEM constructed based on the integrated model. Future research directions are discussed.

Influence of Student Ability, Locus of Control, and Type of Instructional Control on Performance and Confidence

AbstractThis study examined the effects of student ability, locus of control, and type of instructional control on performance and the motivational outcome of confidence. Subjects were randomly assigned to one of two treatments: learner control over the instructional strategy of a computer-based lesson and program control over the instructional strategy of the lesson. Student ability and locus of control were considered as aptitude variables. Upon completion of the lesson, subjects completed a survey designed to measure their confidence and took a posttest to determine if they could identify the concepts presented in the lesson. Results indicated that student ability and locus of control significantly influenced both performance and confidence, whereas type of instructional control did not affect outcomes. Implications for future learner control research are discussed.

A Model for Motivationally Adaptive Computer-Assisted Instruction

AbstractUntil now, the matching of teaching processes to cognitive aspects of learning has been in the foreground of discussions in the field of computer-assisted instruction (CAI). There has been little effort to match teaching processes to the motivational dynamics of the learners. This study will attempt to show how theories and empirical findings of research on motivation can be integrated in a formal model in order to describe and predict motivation within the framework of motivationally adaptive computer-assisted instruction. This article begins with a discussion of problems in CAI and the reasons for these problems. The middle section of this article contains the theoretical basis for the study, which includes the components of a formal model to be implemented as a computer simulation. This article concludes with an example of how computer simulation can represent and predict motivational processes in instructional situations.

What is Motivational Design

There can be contradictory views of what the inherent nature of motivation is. On the one hand it can be unstable, like a pile of dry leaves that changes with every breeze. This makes motivational design highly challenging. Even though you might be able to create a variety of motivational techniques, their effects might be short lived and it would be difficult to predict what motivational states would exist in the learners at any given time. On the other hand, if a person’s motivation is already strong and stable, like a rock, then it would be easier to diagnose the person’s motivational profile and prescribe strategies for change, but it might be more difficult to bring about the changes; you are not likely to motivate people to perform well in situations that are not consistent with their goals. In fact, all of these sometimes seemingly contradictory attributes have to be taken into consideration in the motivational design process. Human motivation is complex and multidimensional, but a great deal has been learned about it and the knowledge can be incorporated into a systematic design process. The purpose of this chapter is to explain the concept of motivational design, describe a model for classifying approaches to motivational design, and discuss several related issues and challenges.

The Arcs Model of Motivational Design

Typically, even though they have years of experience as students and can potentially list motivating versus demotivating events, people feel that they do not have a reasoned, systematic approach to dealing with the motivational aspects of instructional design and teaching. Some people have a great deal of talent and are highly successful based on their experience and, perhaps, charisma, but they might be more limited in their repertoire than they wish they were. The specific aim of the ARCS motivation model is to provide guidance for creating answers to these questions. This chapter provides an introduction to the ARCS model and serves as a foundation for the remaining chapters which are, for the most part, elaborations of the points made in this chapter. The first part of this chapter contains a description of the motivational variables and sample strategies that comprise the four categories of the ARCS model, the second part covers the systematic design process, and the final part discusses the relationship between motivational design and instructional design.