Deconstructing persuasiveness of strategies in behaviour change systems using the ARCS model of motivation

ABSTRACT Persuasive technologies (PTs) motivate behaviour change using various persuasive strategies. However, there is still a dearth of knowledge on how PTs motivate behaviour change and how to design systems to increase their persuasiveness. To provide empirical insight into the mechanism through which PTs persuade, we conducted a large-scale study with 543 participants to investigate the relation between Attention, Relevance, Confidence, and Satisfaction constructs from the ARCS model of motivation and 10 strategies that are commonly used in persuasive systems design. Our results show that the ARCS constructs collectively explain between 82% and 91% of the variance in persuasiveness across the ten strategies. Relevance, followed by Attention, has the strongest association with persuasiveness. The result generalises across gender groups. Therefore, to increase a system’s persuasiveness, designers should focus on designing to increase relevance and to capture user’s attention, while also promoting confidence and a feeling of satisfaction. We contribute to Human–Computer Interaction (HCI) and Persuasive Technology by offering design guidelines for PTs to increase their persuasiveness and hence efficacy.

[1]  G. Fong,et al.  Reductions in HIV risk-associated sexual behaviors among black male adolescents: effects of an AIDS prevention intervention. , 1992, American journal of public health.

[2]  Rita Orji,et al.  Persuasion and Culture: Individualism-Collectivism and Susceptibility to Influence Strategies , 2016, PPT@PERSUASIVE.

[3]  Amirrudin Kamsin,et al.  Game Rhetoric: Interaction Design Model of Persuasive Learning for Serious Games , 2015, HCI.

[4]  Nilufar Baghaei,et al.  Physical activity motivating games: virtual rewards for real activity , 2010, CHI.

[5]  Ming-Hsiung Ying,et al.  A Game-based Learning System using the ARCS Model and Fuzzy Logic , 2013, J. Softw..

[6]  Harri Oinas-Kukkonen,et al.  Exploring Perceived Persuasiveness of a Behavior Change Support System: A Structural Model , 2012, PERSUASIVE.

[7]  Manfred Tscheligi,et al.  The Persuasive Potential Questionnaire (PPQ): Challenges, Drawbacks, and Lessons Learned , 2016, PERSUASIVE.

[8]  Elke E. Mattheiss,et al.  Using Player Type Models for Personalized Game Design - An Empirical Investigation , 2016, IxD&A.

[9]  J. Keller Development and use of the ARCS model of instructional design , 1987 .

[10]  J. Eccles,et al.  Expectancy-Value Theory of Achievement Motivation. , 2000, Contemporary educational psychology.

[11]  Sylvia Tumelo Nthutang,et al.  Identifying E-Learning Components at North-West University, Mafikeng Campus , 2017 .

[12]  E. A. Locke,et al.  Goal setting theory. , 2012 .

[13]  学 加納,et al.  Partial Least Squares Regression を用いた蒸留塔製品組成の推定制御 , 1998 .

[14]  L. Santilli,et al.  Using an Interactive Computer Game to Increase Skill and Self-Efficacy Regarding Safer Sex Negotiation: Field Test Results , 1997, Health education & behavior : the official publication of the Society for Public Health Education.

[15]  Julita Vassileva,et al.  LunchTime: a slow-casual game for long-term dietary behavior change , 2013, Personal and Ubiquitous Computing.

[16]  Claude Frasson,et al.  Assessment of Learners' Motivation during Interactions with Serious Games: A Study of Some Motivational Strategies in Food-Force , 2012, Adv. Hum. Comput. Interact..

[17]  Julita Vassileva,et al.  Tailoring persuasive health games to gamer type , 2013, CHI.

[18]  J. Gerring A case study , 2011, Technology and Society.

[19]  Kien Tsong Chau,et al.  Designing a Motivated Tangible Multimedia System for Preschoolers , 2017 .

[20]  Azman Azid,et al.  FLOOD RISK PATTERN RECOGNITION BY USING ENVIRONMETRIC TECHNIQUE: A CASE STUDY IN LANGAT RIVER BASIN , 2015 .

[21]  Corrie van der Lelie,et al.  The value of storyboards in the product design process , 2006, Personal and Ubiquitous Computing.

[22]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[23]  Julita Vassileva,et al.  Modeling the efficacy of persuasive strategies for different gamer types in serious games for health , 2014, User Modeling and User-Adapted Interaction.

[24]  Galia Angelova,et al.  From Gamification to Gameful Design and Gameful Experience in Learning , 2015 .

[25]  Rita Orji,et al.  Why Are Persuasive Strategies Effective? Exploring the Strengths and Weaknesses of Socially-Oriented Persuasive Strategies , 2017, PERSUASIVE.

[26]  Elke E. Mattheiss,et al.  More than Sex: The Role of Femininity and Masculinity in the Design of Personalized Persuasive Games , 2016, PERSUASIVE.

[27]  Chrysanne Di Marco,et al.  Towards Personality-driven Persuasive Health Games and Gamified Systems , 2017, CHI.

[28]  Rebecca E. Grinter,et al.  Let's play!: mobile health games for adults , 2010, UbiComp.

[29]  Rita Orji,et al.  Personalized Persuasive Messaging System for Reducing Patient's Dissatisfaction With Prolonged Waiting Times , 2016, PPT@PERSUASIVE.

[30]  MarkopoulosPanos,et al.  Personalizing persuasive technologies , 2015 .

[31]  Gustavo Fortes Tondello,et al.  Understanding Player Attitudes Towards Digital Game Objects , 2015, CHI PLAY.

[32]  Johann Schrammel,et al.  Exploring the Links Between Persuasion, Personality and Mobility Types in Personalized Mobility Applications , 2017, PERSUASIVE.

[33]  Claude Frasson,et al.  Players' Motivation and EEG Waves Patterns in a Serious Game Environment , 2010, Intelligent Tutoring Systems.

[34]  H. Kaiser A second generation little jiffy , 1970 .

[35]  Rita Orji,et al.  Exploring the Persuasiveness of Behavior Change Support Strategies and Possible Gender Differences , 2014, BCSS@PERSUASIVE.

[36]  S. Sundar,et al.  Personalization versus Customization: The Importance of Agency, Privacy, and Power Usage , 2010 .

[37]  Abdul Nasir Zulkifli,et al.  INTERACTIVE PERSUASIVE LEARNING ELEMENTS AMONG ELDERLY: A MEASUREMENT MODEL , 2015 .

[38]  Frank Bentley,et al.  Comparing the Reliability of Amazon Mechanical Turk and Survey Monkey to Traditional Market Research Surveys , 2017, CHI Extended Abstracts.

[39]  E. Kupek,et al.  Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders , 2006, BMC medical research methodology.

[40]  David W. McDonald,et al.  Theory-driven design strategies for technologies that support behavior change in everyday life , 2009, CHI.

[41]  Harri Oinas-Kukkonen,et al.  Persuasive Systems Design: Key Issues, Process Model, and System Features , 2009, Commun. Assoc. Inf. Syst..

[42]  Claude Frasson,et al.  Physiological Evaluation of Attention Getting Strategies during Serious Game Play , 2011, AIED.

[43]  Magnus Bång,et al.  The PowerHhouse: A Persuasive Computer Game Designed to Raise Awareness of Domestic Energy Consumption , 2006, PERSUASIVE.

[44]  S. Paxton,et al.  An evaluation of a body image intervention based on risk factors for body dissatisfaction: a controlled study with adolescent girls. , 2009, The International journal of eating disorders.

[45]  Bin Xu,et al.  Personality-targeted Gamification: A Survey Study on Personality Traits and Motivational Affordances , 2016, CHI.

[46]  Boris E. R. de Ruyter,et al.  Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles , 2015, Int. J. Hum. Comput. Stud..

[47]  Rita Orji,et al.  Personalizing Persuasive Strategies in Gameful Systems to Gamification User Types , 2018, CHI.

[48]  Gregory D. Abowd,et al.  Storyboarding: an empirical determination of best practices and effective guidelines , 2006, DIS '06.

[49]  Rik Crutzen,et al.  Effects of a Web-Based Computer-Tailored Game to Reduce Binge Drinking Among Dutch Adolescents: A Cluster Randomized Controlled Trial , 2016, Journal of Medical Internet Research.

[50]  R. Orji,et al.  DESIGN FOR BEHAVIOUR CHANGE: A MODEL-DRIVEN APPROACH FOR TAILORING PERSUASIVE TECHNOLOGIES , 2014 .

[51]  Karen Brown,et al.  Nutritional awareness and food preferences of young consumers , 2000 .

[52]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[53]  Julita Vassileva,et al.  Gender, Age, and Responsiveness to Cialdini's Persuasion Strategies , 2015, PERSUASIVE.

[54]  Mickaël Gardoni,et al.  Persuasive Technologies for Efficient Adaptable Self-Education Kids Smart Mobile School Project , 2016 .

[55]  Boris E. R. de Ruyter,et al.  Adaptive Persuasive Systems: A Study of Tailored Persuasive Text Messages to Reduce Snacking , 2012, TIIS.

[56]  Margaret E. Beier,et al.  Teaching the Biological Consequences of Alcohol Abuse through an Online Game: Impacts among Secondary Students , 2012, CBE life sciences education.

[57]  Kimberly Craig,et al.  Motivation in Instructional Design , 2018 .

[58]  Cristina Hava Muntean,et al.  Measurement and Analysis of Learner’s Motivation in Game-Based E-Learning , 2012 .

[59]  B. Fogg The ethics of persuasive technology , 2003 .

[60]  Cindy M. Gray,et al.  Football Fans in Training: the development and optimization of an intervention delivered through professional sports clubs to help men lose weight, become more active and adopt healthier eating habits , 2013, BMC Public Health.

[61]  S. Schinke,et al.  Alcohol Abuse Prevention Among High-Risk Youth , 2005, Journal of prevention & intervention in the community.

[62]  James Noble,et al.  A Qualitative Study of Culture and Persuasion in a Smoking Cessation Game , 2008, PERSUASIVE.

[63]  Jukka Riekki,et al.  A Case Study on an Ambient Display as a Persuasive Medium for Exercise Awareness , 2008, PERSUASIVE.

[64]  Rik Crutzen,et al.  A Web-based computer-tailored game to reduce binge drinking among 16 to 18 year old Dutch adolescents: development and study protocol , 2014, BMC Public Health.

[65]  H. Oinas-Kukkonen,et al.  Persuasive Features in Web-Based Alcohol and Smoking Interventions: A Systematic Review of the Literature , 2011, Journal of medical Internet research.

[66]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[67]  Rita Orji,et al.  Recommender Systems for Personalized Gamification , 2017, UMAP.

[68]  Kiemute Oyibo,et al.  Investigation of the Persuasiveness of Social Influence in Persuasive Technology and the Effect of Age and Gender , 2017, PPT@PERSUASIVE.

[69]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[70]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[71]  Sangeeta Malik,et al.  Effectiveness Of Arcs Model Of Motivational Design To Overcome Non Completion Rate Of Students In Distance Education , 2014 .

[72]  Wenxin Liu,et al.  Design a cross-training policy to increase satisfaction and decrease cost , 2012, 2012 24th Chinese Control and Decision Conference (CCDC).

[73]  Pradeep Buddharaju,et al.  NEAT-o-Games: blending physical activity and fun in the daily routine , 2008, CIE.

[74]  Edwin A. Locke,et al.  New developments in goal setting and task performance. , 2013 .

[75]  D. Pittet,et al.  Improving Hand Hygiene Compliance in Healthcare Settings Using Behavior Change Theories: Reflections , 2013, Teaching and learning in medicine.

[76]  Charles M. Reigeluth,et al.  Instructional Design Theories and Models : An Overview of Their Current Status , 1983 .

[77]  Andrés Lucero,et al.  Molarcropolis: a mobile persuasive game to raise oral health and dental hygiene awareness , 2009, Advances in Computer Entertainment Technology.

[78]  Judith Masthoff,et al.  Personalising Healthy Eating Messages to Age, Gender and Personality: Using Cialdini's Principles and Framing , 2017, IUI Companion.

[79]  G. Bodenhausen,et al.  Personalized Persuasion , 2012, Psychological science.

[80]  Joel Epstein,et al.  The Impact of a Science Education Game on Students’ Learning and Perception of Inhalants as Body Pollutants , 2011, Journal of science education and technology.

[81]  E. Deci,et al.  Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. , 2000, The American psychologist.

[82]  W. Kernohan,et al.  Applying the ARCS design model to breastfeeding adviceby midwives in order to motivate mothers to personalisetheir experience , 2014 .

[83]  Rita Orji,et al.  Persuasive technology for health and wellness: State-of-the-art and emerging trends , 2018, Health Informatics J..

[84]  Siddharth Suri,et al.  Conducting behavioral research on Amazon’s Mechanical Turk , 2010, Behavior research methods.

[85]  Maria Adler,et al.  Science and human behavior , 2017 .

[86]  Rita Orji,et al.  Persuasive Technology for Reducing Waiting and Service Cost: A Case Study of Nigeria Federal Medical Centers , 2016, AfriCHI.

[87]  Julie A. Kientz,et al.  Personality and Persuasive Technology: An Exploratory Study on Health-Promoting Mobile Applications , 2010, PERSUASIVE.