The role of situational interest in game-based learning Antti Koskinen 1, Jake McMullen 2, Hilma Halme 2, Minna Hannula-Sormunen 2, Manuel Ninaus 3 and Kristian Kiili 1 1 Tampere University, Kalevantie 4, Tampere, 33100, Finland 2 University of Turku, Turku, 20014, Finland 3 University of Innsbruck, Innrain 52, Innsbruck, 6020, Austria Abstract Previous research has emphasized the important role of interest in education. However, only a few studies have investigated situational interest in game-based learning environments. Therefore, this study aims to clarify the role of situational interest in game-based mathematics learning by examining its relations with learning outcomes, self-efficacy, and math interest. Ninety-eight 7th-grade participants played the Number Trace rational number learning game for three 45-minute lessons. Pre-and post-tests were used to measure rational number conceptual knowledge and self-reported measures of math interest. Situational interest and self- efficacy were measured within the game environment. Results indicated that situational interest and learning outcomes were positively related. Furthermore, self-efficacy, as well as math interest, were positively related to situational interest. Keywords 1 Situational interest, game-based learning, learning, self-efficacy, individual interest 1. Introduction extensive research, evidence-based justifications, and new assessment methods tailored to the requirements of the novel environment. During At the beginning of the 21st century, digital the past decades, scholars have made tremendous games were seen as an instructional method that efforts justifying game-based learning as a could prominently change the way we see prominent instructional method that could answer instruction [1]. Drawing from the experiences of the needs of modern society [e.g., 2]. Supporting how people interact with commercial games, it propositions of [1], recent meta-analyses have was postulated that using games designed to provided evidence that game-based learning is an enhance the quality of instruction, referred to as effective instructional method that can add value game-based learning, would be an engaging, fun, exceeding conventional instruction [3, 4]. and novel method that can respond to digital Although game-based learning environments natives' learning preferences and ways of thinking are designed to trigger learners’ interest, [1]. In other words, digital game-based learning surprisingly the role and meaning of interest in was argued to be an effective and interesting game-based learning process has not been studied instructional method for students who have grown sufficiently yet. In fact, none of the recent reviews up in the digital era. or meta-analyses on game-based learning have To convert requirements of the curriculum to a featured interest as a topic, sub-topic, or novel instructional environment requires 6th International GamiFIN Conference 2022 (GamiFIN 2022), April 26-29, 2022, Finland EMAIL: antti.koskinen@tuni.fi (A. Koskinen); jamcmu@utu.fi (J. McMullen); hilma.halme@utu.fi (H. Halme); mimarha@utu.fi; (M. Hannula-Sormunen); manuel.ninaus@uibk.ac.at (M. Ninaus); kristian.kiili@tuni.fi (K. Kiili) ORCID: 0000-0002-9755-1057 (A. Koskinen); 0000-0002-7841- 7880 (J. McMullen); 0000-0002-4357-5977 (H. Halme); 0000- 0002-6106-2569 (M. Hannula-Sormunen); 0000-0002-4664-8430 (M. Ninaus); 0000-0003-2838-6892 (K. Kiili) ©️ 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org) 54 moderator in analysis [e.g., 2, 3, 4]. Moreover, [5] determining how interaction with the learning review of the theoretical foundations in environment are experienced and whether gamification, serious games, and game-based situational interest is enhanced or not [18, 19]. learning show that only four studies were based Theoretically, the expectancy-value model of on interest theories, whereas self-determination achievement choices [20] posits that expectations theory was utilized in 82 studies and flow theory of success (consisting partly of self-efficacy) and in 47 studies. However, ample research evidence subjective task value (consisting partly of from studies conducted in non-game-based individual interest) directly influence engagement learning environments indicate that interest is an with the task and, thus, how situational interest is important motivational factor that substantially experienced. Therefore, individual interest and contributes to learning and motivation [e.g., 6]. self-efficacy can be seen to efficiently reflect the Since interest can be dependent on specific key factors influencing situational interest. environmental stimuli, it is important to examine Previous investigations in non-game-based the role of situational interest also in game-based learning contexts found that situational interest learning as a way to advance our understanding of affects the learning process by enhancing motivational mechanisms in game-based learning. cognitive and affective components [21]. That is, enhanced situational interest can result in 1.1. The role of interest in learning increased engagement [22], attention [21], persistence [21], and lead to improved learning [23]. Moreover, situational interest, if maintained, Being interested in something is a powerful may develop into individual interest, which can psychological state that can substantially affect have a major influence on one’s later learning learning and motivational outcomes. In fact, experiences and outcomes [6, 11]. Although several motivational questionnaires, such as situational interest appears to be a powerful intrinsic motivation scales [7] and ARCS -model supporter of learning, its role in game-based related scales [8], feature interest as a part of the learning environments may be more multifaceted. construct. However, interest differentiates from other motivational constructs as it is always content-dependent [9, 10]. 1.2. Game-based learning and All individuals are hardwired to develop and interest experience interest at any age and in many contexts [11, 12]. According to prominent interest Game-based learning is expected to, by design, theories, interest is the outcome of an interaction increase students’ situational interest, as it often between a person and environmental stimuli [13, features several potential triggers of interest [24]. 6]. If the interest is predominantly influenced by An examination based on [25] suggestions for the interaction with specific environmental potential triggers of interest (highlighted with stimuli it is called situational interest [6]. italics below) shows that this claim is well Situational interest is a psychological state supported on a theoretical level: digital game- associated with increased attention, effort, based learning is a relatively novel instructional enjoyment, and concentration while engaging approach, which provides challenge [24], induces with particular content [9]. In instructional emotions [26], and provides possibilities for settings, this state reflects the learner's interest group work [27] and trying out new roles that towards for example mathematics, but also how make it possible to identify oneself as a character, the learning material is presented [10]. Therefore, thereby creating ownership [24]. In addition, situational interest is always enhanced by the digital game-based learning environments usually interaction with a combination of the features of use incentive structures, such as stars, points, the learning environments [14]. A person’s leaderboards, badges, and trophies, as well as interaction with these features is affected by past game mechanics that can trigger and help experiences that, partly, determine reactions to maintain interest [24]. In fact, [28] found that, in these features and thus experienced interest [10, 12 of 14 studies, students reported more interest 15]. In particular, past research has identified in simulation and gaming activities than in individual interest, representing an individual’s conventional classroom activities. More recently, enduring trait-like interest [6], and self-efficacy, [29] found that students’ situational interest was representing an individual’s beliefs of how they higher in a game-based writing intervention group will perform in certain tasks [16, 17], as factors than in a non-game-based online writing 55 environment. In addition, [30] demonstrated that 1. What is the relation between situational game-based learning can be used to increase interest and learning in game-based math interest in learning mathematics. Based on these learning? theoretical and empirical considerations, it According to previous research findings appears that digital game-based learning is a situational interest can lead to enhanced learning environment that features several engagement [22], attention [21], and persistence characteristics that foster interest and the unique [21] all of which are important factors combination of these characteristics is not usually contributing to learning. In fact, results from found in other instructional environments. different instructional settings, for example, Accordingly, game-based learning may be an computer simulation [38], problem-based ideosyncratic learning environment regarding learning [23], and interactive exhibitions in situational interest. museums [39] suggest that situational interest and Situational interest may have similar learning are positively related. However, in the manifestations and influences in game-based game-based learning domain, the study results are learning than in non-game learning environments. mixed [35, 36, 37, 32]. As most of the research Studies have shown that interaction with the evidence suggests positive relation, we expect that mechanics of game-based learning environments situational interest and learning to be positively has a significant effect on situational interest. For related in game-based math learning (H1). example, manipulation of game mechanics [31] or 2. What is the relation between situational scaffolding [32] affected situational interest. interest and math interest in game-based math Moreover, [33] demonstrated that, in game-based learning? math learning, individual math interest was Studies conducted in different instructional positively related to situational interest, and [34] settings show that individual interest is positively showed that self-efficacy is positively related to related to situational interest [e.g., 23, 18]. In situational interest in game-based learning. game-based math learning, [33] found that high However, past research shows mixed results individual interest in math was related to high and regarding the relation between situational interest maintained situational interest during the and learning in game-based learning. [35] found gameplay. Thus, we expect individual math that situational interest was positively related to interest and situational interest to be positively learning, but [32] found no relation between related in game-based math learning (H2). interest and learning. Moreover, [36] reported that 3. What is the relation between situational situational interest was positively related to the interest and self-efficacy in game-based math post-test score, however, [37] did not find such a learning? relation. Based on these considerations, it is Studies conducted in different instructional important to advance our understanding of the settings show that self-efficacy is generally relation between situational interest and learning positively related to situational interest [38]. in game-based learning. However, [40] found contradictory results; students' initial high self-efficacy predicted a 1.3. The present study decrease in students’ situational interest. In game- based learning context, [34] found that initial mastery experience (i.e., self-efficacy) in a Given the unique motivational characteristics dancing game positively correlated with of game-based learning environments, and the situational interest. Accordingly, we expect self- influence of environmental features on situational efficacy and situational interest to be positively interest, examining the role of situational interest related in game-based math learning (H3). in game-based learning will add valuable insight into the components influencing the effectiveness of game-based learning. This study contributes to 1.4. Participants the current body of literature on game-based learning and situational interest by investigating 98 (49 female, 49 male) Finnish 7th grade how situational interest and learning are related students (M = 13,2 years, SD = 0.36) from nine and how individual math interest and self-efficacy schools participated in the study. The nine schools are related to situational interest. Accordingly, were from varying socioeconomic status (SES) three research questions are examined: areas from a city located in southern Finland. All participants had parental permission to participate 56 in the study. Ethical board and municipality non-symbolic rational number estimation tasks approval were granted for this study. Only and basic arithmetic with non-symbolic rational participants who had completed the pretest and numbers. The third game world included mainly finished at least two game-worlds were included cross-notation tasks aimed at developing an in the study. understanding of the relation between notations. 1.5. Description of the Number Trace -game The Number Trace game is based on the number line estimation task, in which students estimate the spatial position of a target number on a horizontal number line (e.g., where does 3/7 locate on a number line ranging from 0 to 1) [41]. Number line-based instruction has been an effective instructional method to support conceptual rational number understanding [42, 43, 44] and it is also successfully applied in game- based learning [45, 46]. In the game, the player controls a dog on a number line and tries to find bones hidden in the ground. The location of the bones is determined by a given magnitude of a rational number (a target number). Different kinds of representations can be used as target numbers (e.g., symbolic, and non-symbolic fractions, mixed numbers, decimals, whole numbers, and equations). The game was designed to support the development of 7th graders’ rational number understanding based on the Finnish national core curriculum and theories of adaptive expertise with rational numbers [47]. Figure 1 shows three types of tasks featured in the game: i) basic number line estimation, ii) unbounded number line estimation, and iii) number line-based arithmetic tasks. The unbounded number line has no labeled endpoint, but a single unit distance (e.g., 0–1/4; see Figure 1 bottom) in addition to the start point [48]. Different combinations of rational number representations and task configurations were used to support a deep understanding of rational number properties as well as foster situational interest. For example, figure 1 shows an example Figure 1: Examples of tasks included in the game. of an unbounded number line estimation task that Top: Symbolic fraction estimation task. Middle: includes cross-notation (fractions and decimals) non-symbolic addition tasks. Bottom: unbounded and an example of a non-symbolic addition task. cross-notation number line estimation task. The game consisted of three game worlds, with six, seven, and eight levels, respectively. Each The students received immediate feedback for level consisted of ten tasks, and the students could their answers. The player lost virtual energy for complete each game level only once. The first inaccurate estimates and was provided emotional game world included symbolic fraction and feedback – the dog avatar was upset. In the case decimal number tasks that were designed to of accurate estimates, students scored points strengthen students’ basic rational number based on their estimation accuracy, and emotional understanding. The second game world included feedback was provided – the dog avatar was 57 happy. Delayed feedback was provided after Math interest was measured during the pretest completing a level – students could earn one to with a scale derived from the TIMMS test [49]. three stars based on their performance. The scale included nine statements about To further support learning and to foster students’ attitude towards learning mathematics. situational interest, the game provided scaffolds, Reliability for the scale was high (Cronbach’s α = and dynamic difficulty adjustment. Scaffolds 0.93). The math interest variable was calculated were provided after inaccurate answers and as the average value of the scale items. several different scaffolding mechanics were In-game measurement was used to assess utilized. For example, reduction of the fraction to learners’ self-efficacy and situational interest the smallest common factor [35, for more details]. during the gameplay [35, for more details]. This Both adaptive and fixed scaffolding was used. The tool utilized core game mechanics, which adaptation was based on students’ previous presumably allowed learners to maintain game performance in similar tasks. If the game did not flow without interruption. have enough performance data on a certain task Situational interest was measured six times type, fixed scaffolding was used instead. Unlike during the intervention: at the end of the 1st, 4th, adaptive scaffolds, fixed scaffolds were always 5th, 7th, 10th, and 11th game level. The students shown after an inaccurate answer and the used answered the question: “How interesting did you scaffold mechanic was the same for all students. find the tasks in this game level” on a continuous In contrast to scaffolding, dynamic difficulty scale from 0 to 5 (Figure 2). The situational adjustment was used to provide an extra challenge interest variable was calculated as an average to well-performing students. For example, the value of the situational interest measurements. challenge was increased by augmenting the tasks Test-retest approach (Spearman's rank correlation with mathematical traps that had to be avoided coefficient) was used to evaluate the reliability of (locations shown with rational numbers). the repeated one item situational interest measure. The reliability of situational interest was 1.6. Measurements evaluated based on two pairs of situational interest measuring points (levels 4 and 5; levels 10 and 11) that included similar tasks with respect to math The computer-based pre-and post-tests were content. Test-retest reliability ratings for pairs of conducted in regular classrooms by the members situational interest measures were .80 and .59 of the research team. The items measuring rational (indicating good and acceptable reliability, number understanding had a fixed time limit. respectively), Overall, these ratings indicate Pretest and posttest scores were calculated as acceptable reliability considering the content- the average of the correct answers. Pre-and post- dependent nature of situational interest, and the tests included 34 items. Eight number line small variation in the scale. estimation tasks; four items on a 0-1 number line Self-efficacy was measured at the beginning of and four items on a 0-5 number line. Both of these each of the two-game worlds. Students answered featured two decimal and two fraction tasks. the question: “I will certainly perform well on the Students’ answer was scored as correct if the forthcoming tasks.” on a continuous scale from 0 accuracy was over 92% in number line 0-1, and to 5. Self-efficacy was calculated as an average of over 90% in number line 0-5. Eight conversion the self-efficacy measurements. Test-retest tasks (convert 3/5 to a decimal number or convert reliability rating for self-efficacy was .63. This is 0.4 to a fraction number); four items of the acceptable when considering that the first fraction to decimal conversions and four items of measure was authored before the participants had decimal to fraction conversions. Six ordering played the game and the second when participants tasks (arrange 0.5; 1/4, 5/7, 0.356 in order from had experience with the demands of the game. smallest to largest). Twelve rational number arithmetic procedures tasks (e.g., 1/4 × 4; 0.5 ÷ 2). The reliability for the pretest was good (Cronbach’s α = .80), and the reliability for the post-test was acceptable (Cronbach’s α = .76). The learning variable was calculated by subtracting the average of pretest scores (M = .53, SD = .22) from the average of post-test scores (M = .63, SD = .20). 58 Table 1 shows that situational interest and learning were positively related in game-based math learning, thus H1 was confirmed. A multiple regression analysis was conducted to examine whether math interest and self-efficacy were uniquely related to situational interest. Together math interest and self-efficacy explained 38% of variance in situational interest, F(2, 95) = 29.13, p < .001. Math interest was positively related to situational interest (β = .26, p < .05) after controlling for self-efficacy, thus confirming H2. Self-efficacy was positively related to situational interest (β = .48, p < .001), after controlling for Figure 2: Utilized in-game measurement of math interest, thus H3 was confirmed. situational interest 3. Discussion, limitations and 1.7. Procedure conclusion The study was conducted in mathematics This study examined the relation between lessons during regular school days. The pre- and situational interest and learning and how post-tests were administered by the members of individual math interest and self-efficacy relate to the research team. The pretest was carried out a situational interest in game-based learning. As week before the start of the intervention and the expected, situational interest and learning were posttest was conducted a week after the positively related. Our results indicate a similar intervention. The teachers were asked not to teach moderate positive relation between situational rational numbers during the study. The students interest and learning as found previously in played the Number Trace -game for three 45- problem-based and experiential learning minute sessions within a two-week period. environments [23, 39]. Regarding the previous mixed results in the game-based learning context, 2. Results our result supports the finding of [35] who found a positive relation between learning and Descriptive statistics and correlations are situational interest. One reason for the mixed shown in Table 1. results reported in previous studies can be the differences between measurement methodologies. Table 1 Similar to the present study, [35] measured Descriptive statistics and correlations, **< 0.05; situational interest within the game, while studies ** < 0.01 measuring situational interest after the game reported a non-significant relation between Variables 1. 2. 3. 4. situational interest and learning [32, 37]. This 1. Situational - might suggest that measuring situational interest interest within the game, reflects the fluctuating nature of 2. Self- .57** - situational interest better than post-game efficacy measurement. Future studies should examine 3. Math .42** .34** - differences between the measurement interest methodologies of situational interest. 4. Learning .28* .23* .06 - Based on our results, we cannot determine if M 3.50 3.49 2.74 .12 situational interest is an outcome or antecedent of learning, or both. For example, situational interest SD .88 .95 .71 .11 may influence learning by enhancing attention, Range 1-5 1-5 1-4 0-1 concentration, and persistence [21, 22]. On the Skewness -.06 -.39 -.49 .13 other hand, learning may affect situational Kurtosis -.49 .00 -.43 -.57 interest, for example, by creating a positive mood that increases situational interest [19, 32]. The most plausible explanation might be that both of 59 these arguments are true and there is a reciprocal Despite these limitations, the results of this relation between situational interest and learning. study increase our understanding of the role of Consistent with previous studies [18, 23, 33, situational interest in game-based learning and 34], situational interest was positively related to thus advance our understanding of components both math interest and self-efficacy. However, the affecting the effectiveness of game-based relation between math interest and situational learning. Specifically, situational interest and interest was relatively low in the current study. learning outcomes are related in game-based This might indicate that students’ math interest learning. Furthermore, the results indicate that the mainly reflects students’ previous experiences of relation between math interest and situational non-game-based learning environments, and it interest was relatively low. This suggests, that the does not profoundly reflect the situational interest game designers should not only focus on experienced in the game-based learning improving the mere learning outcomes of the environments. On the other hand, students’ games, but also consider how game-based individual interest mathematics in general may learning can be utilized to spark interest in differ from their individual rational number students who do not find learning of the topic interest in a particular learning context. otherwise interesting. For example, if we can Nevertheless, situational interest experienced in spark students’ interest in game-based math the game-based learning environments might be learning, this can possibly enhance their interest more related to the interestingness of the game also in non-game-based math learning [6] and than the instructional content itself. However, as thus make students realize their full learning this study does not give a direct answer for this potential [11]. conjecture, future studies should examine sources of situational interest more exhaustively in game- 4. Acknowledgements based learning. It is important to consider the limitations of This research was funded by the Academy of this study. The intervention was carried out in an Finland (grant numbers 326618, and 310338) and authentic classroom setting and thus it is probable the Strategic Research Council (SRC) established that several students did not manage to complete within the Academy of Finland (grant number all the required game levels to be included in the 336068). analysis. We could not identify the reasons why some students did not manage to complete the game. However, we can assume some reasons: a) 5. References the game may have featured too many rational number tasks for the students and they may not [1] M. Prensky, Digital game-based learning, have had the competence and persistence to Comput. Entertain. 1 (2003) 21–21. complete the levels in the allocated time, b) the doi:10.1145/950566.950596 students’ slow progress in the game may have [2] E. A. Boyle, T. Hainey, T. M. Connolly, G. been the result of low interest in the content, in Gray, J. Earp, M. Ott, ... & J. Pereira, J, An game-based learning, or in the game genre, update to the systematic literature review of graphics, or user interface, c) as the intervention empirical evidence of the impacts and was carried out with computers, technological outcomes of computer games and serious problems (bad network, updates, etc.) may have games, Comput. Educ. 94 (2016) 178–192. caused some students to not complete the required doi:10.1016/j.compedu.2015.11.003 levels. In any case, the sample with adequate data [3] P. Wouters, C. van Nimwegen, H. van was lower than expected. Therefore, we could not Oostendorp & E. D. van Der Spek, A meta- use growth curve modelling and all situational analysis of the cognitive and motivational interest and self-efficacy measurements were effects of serious games, J. Educ. Psychol. collapsed into sum variables. This restricted our 105 (2013) 249–265. doi:10.1037/a0031311 analyses but permitted us to formulate a general [4] D. B. Clark, E. E. Tanner-Smith & S. S. overview of this phenomenon with a sufficient Killingsworth, Digital games, design, and sample size. Moreover, the study design restricted learning: A systematic review and meta- making any causal inferences. Therefore, future analysis, Rev. Educ. Res. 86 (2016) 79–122. research should investigate the reciprocal relation doi:10.3102/0034654315582065 between situational interest and learning. [5] J. Krath, L. Schürmann & H. F. Von Korflesch, Revealing the theoretical basis of 60 gamification: A systematic review and S. G. Rayner (Eds.), Self percep. Ablex analysis of theory in research on Publishing, 2001: pp. 239–266. gamification, serious games and game-based [18] A. Tapola, M. Veermans & M. Niemivirta, learning, Comput. Hum. Behav. 125 (2021). Predictors and outcomes of situational doi:10.1016/j.chb.2021.106963 interest during a science learning task, [6] S. Hidi & K. A. Renninger, The four-phase Instruct. Sci. 41 (2013) 1047–1064. model of interest development, Educ. doi:10.1007/s11251-013-9273-6 Psychol. 41 (2006) 111–127. [19] P. J. Silvia, Self-efficacy and interest: doi:10.1207/s15326985ep4102_4 Experimental studies of optimal [7] A. M. Isen & J. Reeve, The influence of incompetence, J Voc. Behav. 62 (2003) 237– positive affect on intrinsic and extrinsic 249. doi:10.1016/S0001-8791(02)00013-1 motivation: Facilitating enjoyment of play, [20] J. S. Eccles & A. Wigfield, From responsible work behavior, and self-control, expectancy-value theory to situated Mot. & Emot. 29 (2005) 295–323. expectancy-value theory: A developmental, doi:10.1007/s11031-006-9019-8 social cognitive, and sociocultural [8] J. M. Keller, Development and use of the perspective on motivation, Contemp. Educ. ARCS model of instructional design, J. Psychol. 61 (2020). Instruct. Develop. 10 (1987) 2–10. doi:10.1016/j.cedpsych.2020.101859 doi:10.1007/BF02905780 [21] M. Ainley, S. Hidi & D. Berndorff, Interest, [9] P. A. O’Keefe, E. J. Horberg & I. Plante, The learning, and the psychological processes multifaceted role of interest in motivation that mediate their relationship, J. educ. and engagement, In: P. A. O’Keefe & J. M. psychol. 94 (2002) 545–561. Harackiewicz (eds.), Sci. Interest., Springer, doi:10.1037/0022-0663.94.3.545 Cham, 2017: pp. 49–67. [22] J. C. Y. Sun & R. Rueda, Situational interest, [10] M. Knogler, Situational interest: A proposal computer self‐efficacy and self‐regulation: to enhance conceptual clarity, In: P. A. Their impact on student engagement in O’Keefe & J. M. Harackiewicz (eds.), Sci. distance education, Brit. J. Educ. Tech. 43 Interest., Springer, Cham, 2017: pp. 109– (2012) 191–204. doi:10.1111/j.1467- 124. 8535.2010.01157.x [11] K. A. Renninger & S. E. Hidi, To level the [23] J. I. Rotgans & H. G. Schmidt, How playing field, develop interest, Policy. individual interest influences situational Insigh. Behav. Brain. Sci. 7 (2020) 10–18. interest and how both are related to doi:10.1177/2372732219864705 knowledge acquisition: A microanalytical [12] P. J. Silvia, Interest—The curious emotion, investigation, J. Educ. Res. 111 (2018) 530– Cur. Direct. Psychol. Sci., 17 (2008) 57–60. 540. doi:10.1080/00220671.2017.1310710 doi:10.1111/j.1467-8721.2008.00548.x [24] J. L. Plass, B. D. Homer, & C. K. [13] A. Krapp, An educational–psychological Kinzer, Foundations of game-based conceptualisation of interest, Int. J. Educ. learning, Educat. Psychol. 50 (2015) 258– Vocat. Guidan. 7 (2007) 5–21. 283. doi:10.1080/00461520.2015.1122533 doi.org:10.1007/s10775-007-9113-9 [25] K. A. Renninger, J. E. Bachrach & S. E. Hidi, [14] M. Ainley, Interest: Knowns, unknowns, and Triggering and maintaining interest in early basic processes, In: P. A. O’Keefe & J. M. phases of interest development, Learn. Cult. Harackiewicz (eds.), Sci. Intrest., Springer, Soc. Interac. 23 (2019). Cham, 2017: pp. 3–24. doi:10.1016/j.lcsi.2018.11.007 [15] A.M. Durik, C. S. Hulleman, & J. M. [26] M. Ninaus, S. Greipl, K. Kiili, A. Lindstedt, Harackiewicz, J. M, One size fits some: S Huber, E. Klein, ... & K. Moeller, Increased Instructional enhancements to promote emotional engagement in game-based interest, Intr. Math. Sci. Learn. (2015) 49–62. learning–A machine learning approach on [16] A. Bandura, Self-efficacy: toward a unifying facial emotion detection data, Comput. Educ. theory of behavioral change, Psychol. review 142 (2019). 84 191 (1977). doi:10.1037/0033- doi:10.1016/j.compedu.2019.103641 295X.84.2.191 [27] H. Y. Sung & G. J. Hwang, A collaborative [17] F. Pajares & D. H. Schunk, Self-beliefs and game-based learning approach to improving school success: Self-efficacy, self-concept, students' learning performance in science and school achievement, In: R. J. Riding & 61 courses, Comput. Educ. 63 (2013) 43–51. Educ. Psychol. 105 (2013). doi:10.1016/j.compedu.2012.11.019 doi:10.1037/a0032688 [28] J. M. Randel, B. A. Morris, C. D. Wetze & [38] M. Niemivirta & A. Tapola, Self-efficacy, B. V. Whitehill, The effectiveness of games interest, and task performance: Within-task for educational purposes: A review of recent changes, mutual relationships, and predictive research, Simul. Gaming. 23 (1992) 261– effects, Z. Pädagog. Psychol. 21 (2007) 241– 276. doi:10.1177/1046878192233001 250. doi:10.1024/1010-0652.21.3.241 [29] C. C. Liao, W. C. Chang & T. W. Chan, The [39] M. P. Vainikainen, H. Salmi & H. effects of participation, performance, and Thuneberg, Situational interest and learning interest in a game‐based writing in a science center mathematics exhibition, J. environment, J. Comp. Assist. Learn. 34 Res. STEM Educ. 1 (2015) 15–29. (2018) 211–222. doi:10.1111/jcal.12233 doi:10.51355/jstem.2015.6 [30] L. D. Pratama & W. Setyaningrum, Game- [40] K. Nuutila, A. Tapola, H. Tuominen, S. Based Learning: The effects on student Kupiainen, A. Pásztor & M. Niemivirta, cognitive and affective aspects. J. Phys.: Reciprocal Predictions Between Interest, Conf. Ser. 1097 (2018). doi:10.1088/1742- Self-Efficacy, and Performance During a 6596/1097/1/012123 Task, Front. Educ. 5 (2020) 36–49. [31] J. L. Plass, B. D. Homer, E. O. Hayward, J. doi:10.3389/feduc.2020.00036 Frye, T. T. Huang, M. Biles, ... & K. Perlin, [41] R. S. Siegler & J. E. Opfer, The development K. The effect of learning mechanics design of numerical estimation: Evidence for on learning outcomes in a computer-based multiple representations of numerical geometry game, in: E-learn. Games. Train. quantity, Psychol. Sci. 14 (2003) 237–250. Educ. Health. Sports. 2012: pp. 65–71. doi:10.1111/1467-9280.02438 [32] C. H. Chen & V. Law, Scaffolding individual [42] R. S. Siegler, Magnitude knowledge: The and collaborative game-based learning in common core of numerical development, learning performance and intrinsic Develop. Sci. 19 (2016) 341–361. motivation, Comput. Hum. Behav. 55 (2016) doi:10.1111/desc.12395 1201–1212. doi:10.1016/j.chb.2015.03.010 [43] D. W. Braithwaite & R. S. Siegler, Putting [33] G. Rodríguez‐Aflecht, T. Jaakkola, N. fractions together. J. Educ. Psychol. 113 Pongsakdi, M. Hannula‐Sormunen, B. (2020) 556–571.doi:10.1037/edu0000477 Brezovszky & E. Lehtinen, The development [44] S. M. Wortha, J. Bloechle, M. Ninaus, K. of situational interest during a digital Kiili, A. Lindstedt, J. Bahnmueller, mathematics game, J. Comput. Assist. Learn. M.Korbinian, & E. Klein, Neurofunctional 34 (2018) 259–268. doi:10.1111/jcal.12239 plasticity in fraction learning: an fMRI [34] C. Huang & Z. Gao, Associations between training study, Trends. Neurosci. Educ. 21 students’ situational interest, mastery (2020). doi:10.1016/j.tine.2020.100141 experiences, and physical activity levels in [45] K. Kiili, K. Moeller, & M. Ninaus, an interactive dance game, Psychol. Health Evaluating the effectiveness of a game-based Med. 18 (2013) 233–241. rational number training-In-game metrics as doi:10.1080/13548506.2012.712703 learning indicators, Comput. Educ. 120 [35] K. Kiili, A. Lindstedt, A. Koskinen, H. (2018) 13–28. Halme, M. Ninaus & J. McMullen, Flow doi:10.1016/j.compedu.2018.01.012 Experience and Situational Interest in Game- [46] M. M. Riconscente, Results from a Based Learning: Cousins or Identical Twins, controlled study of the iPad fractions game I. J. Ser. Games. 8 (2021) 93–114. Motion Math, Games. Cult. 8 (2013) 186– doi:10.17083/ijsg.v8i3.462 214. doi:10.1177/1555412013496894 [36] J. L. Nietfeld, L. R. Shores & K. F. [47] J. McMullen, M. M. Hannula-Sormunen, E. Hoffmann, Self-regulation and gender within Lehtinen & R. S. Siegler, Distinguishing a game-based learning environment, J. Educ. adaptive from routine expertise with rational Psychol. 106 (2014). number arithmetic, Learn. Instruct. 68 [37] J. L. Plass, P. A. O'Keefe, B. D. Homer, J. (2020). Case, E. O. Hayward, M. Stein & K. Perlin, doi:10.1016/j.learninstruc.2020.101347 The impact of individual, competitive, and [48] S. Jung, S. Roesch, E. Klein, T. collaborative mathematics game play on Dackermann, J. Heller & K. Moeller, K, The learning, performance, and motivation, J. strategy matters: Bounded and unbounded 62 number line estimation in secondary school children, Cogn. Develop. 53 (2020). doi:10.1016/j.cogdev.2019.100839 [49] I.V. S. Mullis, M. O. Martin, P. Foy, & M. Hooper, M, TIMSS 2015 International Results in Mathematics. Retrieved from Boston College, TIMSS & PIRLS International Study Center website: http://timssandpirls.bc.edu/timss2015/intern ational-results/ (2016). 63