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Presence, Involvement, and Flow in Digital Games

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Evaluating User Experience in Games

Part of the book series: Human-Computer Interaction Series ((HCIS))

Abstract

Digital games elicit rich and meaningful experiences for the gamers. This makes games hard to study solely with usability methods that are used in the field of human–computer interaction. Here is presented a candidate framework to analyze multidimensional user experience (UX) in games. Theoretically, the framework is grounded both on previous game studies and on relevant psychological theories. Methodologically, it relies on multivariate data analysis of approximately 320 games (n = 2182), with the aim of revealing the subcomponents of UX in games. The framework captures the essential psychological determinants of UX, namely, its quality, intensity, meaning, value, and extensity. Mapping these determinants to the game mechanics, the narrative and the interface offers a rich view to UX in games and provides added value to those who want to understand why games are experienced in certain ways.

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Acknowledgments

We thank prof. Takashi Kawai, Antti Hulsi, Heikki Särkelä, Jeppe Komulainen, Miikka Lehtonen, Maija Pekkola, Jaakko Sipari, and Jari Lipsanen for help in collecting and analyzing the data and sharing thoughts. This work has been supported by the User Centered Information Technology graduate school, Oskar Öflund’s Foundation and the Kone Foundation.

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Correspondence to Jari Takatalo .

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Appendices

Appendix 1: The Final PFA of the Presence and Involvement Measurement Model

Total variance explained

 

Initial Eigen values

Extraction sums of squared loadings

Rotation

Factor

Total

Percentage of variance

Cumulative percentage

Total

Percentage of variance

Cumulative percentage

Total

Role engagement

19,650

23,674

23,674

19,125

23,042

23,042

9,382

Attention

6,189

7,456

31,130

5,657

6,816

29,858

8,310

Interest

3,394

4,089

35,220

2,811

3,387

33,245

4,235

Importance

2,715

3,271

38,491

2,204

2,656

35,900

10,179

Co-presence

2,025

2,439

40,930

1,496

1,803

37,703

11,823

Interaction

1,803

2,172

43,103

1,193

1,438

39,141

5,613

Arousal

1,782

2,148

45,250

1,147

1,382

40,523

4,498

Physical presence

1,485

1,789

47,040

954

1,150

41,673

11,537

  1. Extraction method: Principal axis factoring.

Appendix 2: The Final PFA of the Flow Measurement Model

Total variance explained

 

Initial Eigen values

Extraction sums of squared loadings

Rotation

Factor

Total

Percentage of variance

Cumulative percentage

Total

Percentage of variance

Cumulative percentage

Total

Valence

13,279

23,713

23,713

12,762

22,788

22,768

7,543

Impressiveness

4,055

7,241

30,955

3,458

6,175

28,963

4,573

Competence

2,540

4,535

35,490

2,020

3,608

32,571

7,453

Challenge

2,013

3,594

39,084

1,445

2,581

35,152

3,272

Enjoyment

1,898

3,371

42,454

1,261

2,252

37,404

4,848

Playfulness

1,695

3,027

45,481

1,140

2,036

39,440

6,707

Control

1,627

2,906

48,387

1,041

1,860

41,298

4,628

  1. Extraction method: Principal axis factoring.

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Takatalo, J., Häkkinen, J., Kaistinen, J., Nyman, G. (2010). Presence, Involvement, and Flow in Digital Games. In: Bernhaupt, R. (eds) Evaluating User Experience in Games. Human-Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84882-963-3_3

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