This source preferred by Raian Ali

Authors: Cham, S., Algashami, A., McAlaney, J., Stefanidis, A., Phalp, K. and Ali, R.

http://eprints.bournemouth.ac.uk/32258/

Start date: 9 April 2019

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 11433 LNCS

Pages: 237-253

eISSN: 1611-3349

ISBN: 9783030172862

ISSN: 0302-9743

DOI: 10.1007/978-3-030-17287-9_20

The concept of goals is prominent in information systems and also artificial intelligence literature such as goal-oriented requirements engineering and self-adaptive systems. Digital motivation systems, e.g. gamification and persuasive technology, utilise the concept of behavioural goals which require a different mind-set on how to elicit and set them up, how to monitor deviation from such goals and how to ensure their completion. Behavioural goals are characterised by a range of factors which are not the main focus in classic information systems and AI literature such as self-efficacy, perceived usefulness. To engineer software supporting goal setting, a concretised taxonomy of goals would help a better-managed analysis and design process. In this paper, we provide a detailed classification of behavioural goals and their associated properties and elements (types, sources, monitoring, feedback, deviation and countermeasures). As a method, we review the literature on goal setting theory and its application in different disciplines. We subsequently develop five reference checklists which would act as a reference point for researchers and practitioners in persuasive and motivational systems.

This data was imported from DBLP:

Authors: Cham, S., Algashami, A., McAlaney, J., Stefanidis, A., Phalp, K. and Ali, R.

Editors: Oinas-Kukkonen, H., Win, K.T., Karapanos, E., Karppinen, P. and Kyza, E.A.

http://eprints.bournemouth.ac.uk/32258/

https://doi.org/10.1007/978-3-030-17287-9

Journal: PERSUASIVE

Volume: 11433

Pages: 237-253

Publisher: Springer

ISBN: 978-3-030-17286-2

This data was imported from Scopus:

Authors: Cham, S., Algashami, A., McAlaney, J., Stefanidis, A., Phalp, K. and Ali, R.

http://eprints.bournemouth.ac.uk/32258/

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 11433 LNCS

Pages: 237-253

eISSN: 1611-3349

ISBN: 9783030172862

ISSN: 0302-9743

DOI: 10.1007/978-3-030-17287-9_20

© Springer Nature Switzerland AG 2019. The concept of goals is prominent in information systems and also artificial intelligence literature such as goal-oriented requirements engineering and self-adaptive systems. Digital motivation systems, e.g. gamification and persuasive technology, utilise the concept of behavioural goals which require a different mind-set on how to elicit and set them up, how to monitor deviation from such goals and how to ensure their completion. Behavioural goals are characterised by a range of factors which are not the main focus in classic information systems and AI literature such as self-efficacy, perceived usefulness. To engineer software supporting goal setting, a concretised taxonomy of goals would help a better-managed analysis and design process. In this paper, we provide a detailed classification of behavioural goals and their associated properties and elements (types, sources, monitoring, feedback, deviation and countermeasures). As a method, we review the literature on goal setting theory and its application in different disciplines. We subsequently develop five reference checklists which would act as a reference point for researchers and practitioners in persuasive and motivational systems.