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Commonly Used Questionnaires and Rating Scales in HCI Research

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In Human-Computer Interaction (HCI) research, various rating scales are commonly used to assess user experience, usability, and other factors. These scales provide vital insights into the interaction between users and computer systems, helping researchers and designers to enhance the effectiveness and intuitiveness of technology. The following list categorizes some of the most popular rating scales used in HCI research, highlighting the specific factors they are designed to assess. Cite this page as follows:

Ahmed Sabbir Arif. 2023. Commonly Used Questionnaires and Rating Scales in HCI Research. University of California, Merced, United States. https://www.theiilab.com/notes/scales.html
Evaluation Instrument Reference
Acceptance Technology (Acceptance Questionnaire) Van Der Laan et al. (1997)
Customer Satisfaction Net Promoter Score (NPS) Reichheld (2003)
Eye/Visual Fatigue Visual Fatigue Questionnaire Heuer et al. (1989)
Flow,
Presence, and
Engagement		 Core Flow Scale Martin & Jackson (2008)
Short Flow Scale Martin & Jackson (2008)
Flow for Presence Questionnaire (FPQ) Redaelli & Riva (2011)
Flow State Scale (FSS) Jackson & Marsh (1996)
Presence Questionnaire (PQ) Witmer & Singer (1998)
Utrecht Work Engagement Scale (UWES) Schaufeli & Bakker (2003)
Game Game Engagement Questionnaire (GEQ) Brockmyer et al. (2009)
Game Experience Questionnaire (GE) IJsselsteijn et al. (2007)
Player Experience Inventory (PXI) Abeele et al. (2020)
Mini Player Experience Inventory (miniPXI) Haider et al. (2022)
Habit Self-Report Habit Index (SRHI) Verplanken & Orbell (2003)
Handedness Edinburgh Handedness Inventory (EHI) Oldfield (1971)
Hedonic and
Pragmatic Qualities		 Modular Evaluation of Components of User Experience (MeCUE) Minge et al. (2017)
Intuitiveness Intuitive Interaction Questionnaire (INTUI) Ullrich & Diefenbach (2010)
Media
Virtual Reality
Augmented Reality		 Immersive Tendencies Questionnaire (ITQ) Witmer & Singer (1998)
Simulator Sickness Questionnaire (SSQ) Kennedy et al. (1993)
Relationship Dyadic Adjustment Scale (DAS) Spanier (1976)
Inclusion of Other in the Self (IOS) Scale Aron et al. (1992)
Relationship Closeness Inventory (RCI) Berscheid et al. (1989)
Satisfaction End-user Computing Satisfaction (EUCS) Doll & Torkzadeh (1988)
Situational
Awareness		 Situational Awareness Rating Technique (SART) Taylor (1989)
Somatic
Symptoms		 Borg's Category-Ratio Scale (CR10) Borg (1998)
Borg's Ratings of Perceived Exertion & Pain (RPE) Borg (1998)
Trust Trust in Automation (TiA) Körber (2019)
Usability After-Scenario Questionnaire (ASQ) Lewis (1995)
AttrakDiff Questionnaire Hassenzahl et al. (2003)
Computer System Usability Questionnaire (CSUQ) Lewis (1995)
Nielsen's Attributes of Usability (NAU) Nielsen (1993)
Nielsen's Heuristic Evaluation (NHE) Nielsen (1993)
Perceived Usefulness and Ease of Use (PUEU) Davis (1989)
Post-Study System Usability Questionnaire (PSSUQ) Lewis (1992)
Practical Heuristics for Usability Evaluation (PHUE) Perlman (1997)
Purdue Usability Testing Questionnaire (PUTQ) Lin et al. (1997)
Questionnaire for User Interface Satisfaction (QUIS) Chin et al. (1988)
System Usability Scale (SUS) Brooke (1996)
Technology Acceptance Model Satisfaction (TAM) Davis (1989)
Usefulness, Satisfaction, and Ease of use (USE) Questionnaire Lund (2001)
User Experience Questionnaire (UEQ) Laugwitz et al. (2008)
Website Website Analysis and MeasureMent Inventory (WAMMI) Kirakowski & Cierlik (1998)
Workload NASA Task Load Index (NASA-TLX) NASA (1986) by Sandra G. Hart
Subjective Workload Assessment Technique (SWAT) Reid & Nygren (1988)

Alternatives to Likert Scale

  1. Constant Sum Scale (CMS) or Points Allocation: Respondents distribute points among items to indicate relative importance or preference.
  2. Dichotomous Scale: A simple two-point scale, like "Yes/No" or "True/False."
  3. Guttman Scale (Guttman, 1944): Involves statements that increase in intensity, assuming agreement with less intense statements implies agreement with more intense ones.
  4. Mokken Scale (Mokken, 2011): A non-parametric model for creating scales from binary items.
  5. Ranking Scale: Respondents rank order items according to a criterion.
  6. Semantic Differential Scale (Osgood et al., 1957): Uses a line with opposing adjectives at each end for rating.
  7. Stapel Scale (by Jan Stapel): Centers around a single adjective rated against a numerical range.
  8. Thurstone Scale (Thurstone, 1928): Involves expert-assigned values to statements, with respondents indicating agreement.
  9. Visual Analogue Scale (VAS): A continuous line where respondents mark their level of agreement or feeling.

Alternatives to Likert Scale for Young Children

  1. Color Scale: Uses different colors to represent different levels of agreement or satisfaction, which is intuitive and engaging for younger children.
  2. Smileyometer (Read & MacFarlane, 2000): A visual scale with a range of smiley faces, from very happy to very sad, for children to indicate their feelings or satisfaction.
  3. Facial Expression Scale (based on Paul Ekman's work): Similar to the Smileyometer, this scale uses a range of facial expressions to gauge feelings or reactions.
  4. Picture Scale: Incorporates pictures or icons that represent different levels of feelings or opinions, suitable for children who are not yet reading.
  5. Sticky Ladder Scale (Airey et al., 2002): Children use stickers or tokens on a ladder-like structure to indicate preferences.
  6. Paper Ladder Scale (Sylla et al., 2017): A paper-based, simpler version of the Sticky Ladder Scale, allowing children to express their preferences in an easy and accessible way.
  7. Thermometer Scale: Uses the metaphor of a thermometer to gauge levels of feeling or satisfaction, with higher temperatures indicating more of a certain feeling.
  8. Token Voting: Children are given a set number of tokens to allocate to different options, indicating their preference or priority.

References

  1. Abeele, V.V., Spiel, K., Nacke, L., Johnson, D. and Gerling, K. 2020. Development and Validation of the Player Experience Inventory: A Scale to Measure Player Experiences at the Level of Functional and Psychosocial Consequences. International Journal of Human-Computer Studies. 135, (Mar. 2020), 102370.
  2. Airey, S., Plowman, L., Connolly, D. and Luckin, R. 2002. Rating Children's Enjoyment of Toys, Games and Media. 3rd World Congress of the International Toy Research Association on Toys, Games and Media (London, U.K., 2002).
  3. Albert, B. and Tullis, T. 2022. Measuring the User Experience: Collecting, Analyzing, and Presenting UX Metrics. Morgan Kaufmann.
  4. Aron, A., Aron, E.N. and Smollan, D. 1992. Inclusion of Other in the Self Scale and the structure of interpersonal closeness. Journal of Personality and Social Psychology. 63, 4 (1992), 596–612.
  5. Berscheid, E., Snyder, M. and Omoto, A.M. 1989. The Relationship Closeness Inventory: Assessing the closeness of interpersonal relationships. Journal of Personality and Social Psychology. 57, 5 (1989), 792–807.
  6. Borg, G. 1998. Borg's Perceived Exertion and Pain Scales. Human Kinetics.
  7. Brockmyer, J.H., Fox, C.M., Curtiss, K.A., McBroom, E., Burkhart, K.M. and Pidruzny, J.N. 2009. The Development of the Game Engagement Questionnaire: A Measure of Engagement in Video Game-Playing. Journal of Experimental Social Psychology. 45, 4 (Jul. 2009), 624–634.
  8. Brooke, J. 1996. SUS: A "Quick and Dirty" Usability. Usability Evaluation in Industry. P.W. Jordan, B. Thomas, I.L. McClelland, and B. Weerdmeester, eds. CRC Press. 189–194.
  9. Chin, J.P., Diehl, V.A. and Norman, K.L. 1988. Development of an Instrument Measuring User Satisfaction of the Human-Computer Interface. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New York, NY, USA, May 1988), 213–218.
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