Playful learning in the twenty-first century: Motivational variables, interest assessment, and games


The motivational terms of engagement, interest, and motivation are usually used interchangeably across disciplines. This trend is problematic because each construct has unique characteristics that either differ or overlap each other, and as a result, empirical works that are unclear about which construct is being measured attributes to muddling the overall quality of the research area on interest development. The issue of interest measurement is further complicated by the increased use of technology and games for learning. The purpose of this literature review is to first provide definitions of engagement, interest, and motivation as well as their relationship to each other in learning. Then, I inspect previous methods used to assess interest and report on the recent assessments of interest development using analog and digital games for learning. Empirical works selected for this literature review directly measuring interest and were recent publications (< 5 years), and a total of seven studies in out-of-school K-12 learning settings were examined in detail. Findings from the literature review show that interest assessment has traditionally relied on self-report measures over a brief period of time, whereas ideally a more accurate representation of interest tracking pairs’ self-report measures with fieldwork across an individual’s lifespan. A common occurrence found in interest assessment studies include small sample groups and an inconsistency in measurements of interest. Further research is needed to develop an instrument or methodology that can measure interest in isolation from other motivational variables and for adaption across disciplines.


What does it mean to be interested in a phenomenon? Motivational variables—interest, engagement, and motivation—are often interchangeably used across domains, which contributes to muddled research reporting. First, the meaning and relationship of each motivational construct are clearly defined and unpacked. Next, interest assessment methods are reviewed, followed by a review of recent empirical studies on situational interest. This article may prove useful to those interested in understanding the nuance of motivational variables, why interest as a construct is important, and for those interested in the design of interest assessment interventions. It is my hope that this work can help address the gaps in interest assessment across disciplines and practices.

Motivation, interest, and engagement

To fully understand interest as a construct, we look to the roots of its discovery. Researchers in the early twentieth century explored motivation through experimentations with cats, dogs, rats, and pigeons, using varying forms of external stimuli that activated reinforced response (Skinner 1948; Thorndike 1911). These animals were taught to perform a specific action (e.g., press down a bar, peck keys) in exchange for a reward (e.g., food, relief from pain). A popular idea of motivation was the law of effect, proposed by Thorndike (1927), who posited that behaviors that produce a satisfying effect will become more likely in that particular situation, and that responses that produce a discomforting effect will become less likely in that situation.

Thorndike hypothesized that learning new behavior through annoying or painful stimuli caused a strong and positive motive to suppress original tendencies and pointed to learning being a stimulus response. Thus, emotions such as anxiety could be a motivator for humans, as anxiety reduction could reinforce desired behavior (Mowrer 1938, 1939). Emphasis was placed on external factors influencing the subject’s motivation and not on the subject’s internal drive or needs; the theory did not account for playful and exploratory behavior commonly exhibited in animals and children. Thus, the motivational concept of competence was introduced to explain these behaviors and results from an effective interaction between the subject and environment (White, 1959). In addition to propelling the stimulus–response theory for motivation, White (1959) observed that an intrinsic drive existed in the sensemaking process of animals and children. Around the same time, Hunt (1965) built upon Jean Piaget’s earlier observations of infants and began to use the term intrinsic motivation to refer to humans imposing control over their environment, an action suggested to be inherently motivating.

The consensus from recent literature involves two aspects: extrinsic motivation (EM) and intrinsic motivation (IM). EM has been defined as the motivation to perform an action to meet an external goal or externally imposed constraint (Hennessey et al. 2014) and doing something as a means to an end (Locke and Schattke 2018; Ryan and Deci 2000; Vallerand and Ratelle 2002). In contrast, IM has been defined as the motivation do something for its own sake (Hennessey et al. 2014), doing something because it is inherently interesting or enjoyable (Ryan and Deci 2000; Vallerand and Ratelle 2002), and liking or wanting an activity divorced from a specific outcome (Locke and Schattke 2018). Hennessey et al. (2014) point to the common misconception that intrinsic motivation is always good and extrinsic motivation should be avoided, and caution that intrinsic motivation can result in both positive and negative outcomes. Instead of treating extrinsic and intrinsic motivation as two separate entities, researchers have argued that the two coexist and work simultaneously to influence behavior positively (Lepper and Henderlong 2000).

Two other constructs are commonly used when discussing games and informal learning: interest and engagement. Within the context of school, Christenson et al. (2012) defined engagement as participation in school and extracurricular activities and commitment to related goals. A more general definition of engagement involves persistence and time spent with specific objects (Ainley et al. 2002). A narrower definition of engagement is the “active, goal-directed, flexible, constructive, persistent, focused interactions with the social and physical environments” whereas disaffection refers to the alienation, rebellion, fear, burnout, and turning away from opportunities of learning for individuals (Furrer and Skinner 2003, p. 149).

Interest has been defined as a psychological state and a tendency to re-engage with particular content over time. In this definition, interest develops through an individual’s interaction with his or her environment (Hidi and Renninger 2006; Krapp 1999, 2007) and has a strong influence on an individual’s cognitive and affective functioning (Ainley et al. 2002; Krapp 1999; Renninger and Hidi 2011; Schiefele 1991). Interest can serve as a counterweight to feelings of disaffection, such as frustration, boredom, and confusion (Thoman et al. 2011). Triggers that work for an individual on the first day may fail to trigger interest on the next.

There are many ways to trigger learner interest, and both the activity and learner characteristics seem to impact that triggering (Renninger and Bachrach 2015). Studies have shown that curiosity and interest activate the reward circuitry in the brain, in particular the caudate in the striatum, an area that was previously associated with anticipated rewards (Gruber et al. 2014; Kang et al. 2009). The literature on interest commonly distinguishes between two types of interest: individual and situational. Individual interest (I-I) has been defined as an individual’s predisposition to attend to certain stimuli, events, and objects (Ainley et al. 2002; Hidi 1990; Schiefele 1991) and as something that develops slowly over time (Hidi 1990). Situational interest (S-I) has been described as a response to the environment (Ainley et al. 2002) or situation (Krapp 1999). An interaction between an individual and his or her environment, in particular after repetition that sparks situational interest, could lead to the development of a well-developed individual interest (Hidi 1990).

Relationships among motivation, engagement, and interest

Motivation, engagement, and interest are constructs that influence each other and facilitate learning. The state of interest is a key element of engagement (Ainley et al. 2002), and the constructs of engagement and interest have been defined as curiosity (Arnone et al. 2011). Arnone and colleagues argue that without engagement, curiosity cannot progress into a well-developed interest, and that technology can play a role in triggering interest and sustaining engagement. Renninger and Bachrach (2015) observed that there has been little cross-referencing between the research of interest development and engagement, and they encourage this field of research, considerably across disciplines.

The relationship between motivation and engagement seems to be reciprocal in nature (Renninger and Bachrach 2015; Singh et al. 2002) and develops from the interaction between an individual and the environment (Barron 2006; Hidi and Renninger 2006; Reschly and Christensen 2012). Research has shown that from 5 to 15 years old, EM reasons (e.g., “I want to please my parents”) replace IM reasons (e.g., “I want to study hard to get into a good school”) for task engagement in school (Chandler and Connell 1987). Similar findings have been observed through the progression of third through eighth or ninth grade (Cordova and Lepper 1996; Harter, 1980, 1981; Lepper et al. 2005; Newman 1990; Tzuriel 1989). It appears that the more time children spend in schools in the United States, the less interest they have in learning for its own sake (Lepper and Henderlong 2000).

Thankfully, increasing motivation can lead to engagement in academic tasks, which is related to achievement (Banks et al. 1978; Dweck 1986) and stresses the importance of motivational variables, such as goal setting, self-efficacy, and self-regulation (Renninger and Bachrach 2015) in classrooms. What engagement occurs prior to triggering interest needs to be further explored. It is still unknown whether each individual is engaging in an activity in the same way, in which manner he or she is engaged (cognitively, behaviorally, affectively), and the impact of varying forms of engagement on continued engagement (Renninger and Bachrach 2015).

Using the past 30 years of interest studies, Renninger and Hidi (2011) describe five situations involving interest as a motivational variable: (1) interest refers to an individual’s focused attention and/or engagement with particular events and objects, (2) interest involves a particular relation between a person and the environment that can be sustained through interaction, (3) interest has both cognitive and affective components, (4) a person is not always aware that his or her interest is being triggered, and (5) brain activations differ when a learner is and is not engaged with interest. The authors continue to state that interest has been recognized as a critical motivational variable that guides attention, facilitates learning across content areas, is applicable for learners of all ages, and develops through experience. In addition, interest shares a reciprocal relation to goal setting, self-efficacy, self-regulation, and achievement value, all of which are motivational variables.

Using these definitions, there is a clear overlap between interest and motivation, the latter of which also draws upon the interaction between an individual and his or her environment. What is of interest can be driven by both EM (e.g., “I am interested in actions that will land me a promotion”) and IM (e.g., “I am interested in improving my photography skills”), which illustrates how motivation and interest can enhance or discourage the development of one another.

Assessing interest

The current research literature on interest development is largely focused on proposing different models of interest, rather than on possible assessments in real-world settings (e.g., Hidi and Renninger 2006; Renninger and Hidi 2011; Schraw and Lehman 2001). Studies concerning interest assessment are largely text-based, assessing relationships between interest and text call (cf. Hidi and Baird 1988; Sadoski et al. 2000; Schiefele and Krapp 1996; Schraw et al. 1995) and the seductiveness, vividness, and coherence features of text (Schraw and Lehman 2001; Wang and Adescope 2016). It is evident that research on interest needs to move beyond text-based studies.

In addition, existing literature on interest and engagement rely largely on self-report measures, which is problematic considering that individuals are not always aware when interest is triggered (Renninger and Bachrach 2015). Yet the merit of self-report measures lie in its quantifiability, allowing researchers to attach the tangible to the intangible and to offer calculable explanations of elusive constructs such as interest (cf. Isaac et al. 1999; Thoman et al. 2011; Tyler-Wood et al. 2010). Other authors argue that observational methods are an effective way to study the triggering of interest, especially when individuals may not be aware that the triggering process is of concern. These authors also point to the complementary nature of observational data for triangulating data from other sources (Renninger and Bachrach 2015).

To make the matter of interest assessment even more complex, the modern individual now interacts with more electronic devices than ever before (e.g., mobile devices, laptops, video games). Are these interactions indicative of interest generation or development? How can all these interactions be captured using alternative methods such as technology and games? Can interest assessment be gamified? Almost 30 years ago, educators worried that edutainment products would overtake entire curriculums and fill students with irrelevant or insignificant information (Trotter 1992). Questions regarding how and where technology most effectively fits into the realm of education and those regarding technology’s impact on learning, are worth exploring for the purposes of reconstructing curriculums to address the demands and needs of the twenty-first century. Videogames are one of the mediums currently being investigated for its adaptability and interactivity (Prensky 2001; Wouters and van Oostendorp 2016) and is one with which most students are familiar (Van Eck 2006). The global market for video games is a billion-dollar business that generates more profit than the movie industry (Ell 2018; Kirriemuir and Mcfarlane 2004). This literature review serves as an initial investigation into situational interest assessment within digital and informal learning environments.


Interest assessment is a relatively new field of research. Interest as an aspect of cognition had historically been neglected in favor of curiosity, motivation, and flow until the 1980s (Hidi 1990; Krapp 1999). It was a challenge to locate studies that included games as the technology medium and interest as research background.

This challenge speaks to the scarcity in this research area. A literature review that examines the relationship between video games and interest still does not exist today, as far as the author is aware. Existing literature reviews focus on mostly positive learning outcomes from games (Boyle et al. 2016; Connolly et al. 2012; Hainey et al. 2016); the use of specific games or game features in education and research (Dondlinger 2007; Evans et al. 2015; Nebel et al. 2017; Qian and Clark 2016); and cognitive perspectives, such as aggression and immersion (Anderson and Bushman 2001; Ferguson 2007; Hamari et al. 2016). Past proposals of videogame contributions included areas of personal and social development, language and literacy, mathematical development, creative development, knowledge and understanding of the world, and physical development (McFarlane et al. 2002).

Articles were drawn from the EBSCO and Scopus databases using the following keywords: informal learning games, situational interest, and interest development for a total of 16 journal articles. Upon further examination, four of the 16 articles explicitly measure S-I as a construct. A total of three additional articles with an out-of-school learning setting were selected from the 16 articles to diversify the sample and methods reviewed (i.e., high-school field trip, summer programs). Given that interest has varying definitions depending on the individual and context (cf. Dohn 2011), I unpack how interest is defined and assessed in each article. This work contributes to a foundational understanding of how S-I and interest overall are being measured in studies utilizing video games.


Assessing interest in out-of-school settings

A total of seven empirical articles were examined for this literature review. Variations include subject domains, age groups, and duration of the intervention (i.e., one-time 50-min session to 6-week public exhibition), all of which are factors to consider when tracking changes in interest. By understanding these recent interest studies that utilize games, we can be informed on what resources are available and/or needed to researchers.

Linnenbrink-Garcia et al. (2013) explored ways in which S-I is supported in the classroom and the academic benefits of situated interest using regression analyses methods, crediting such methods for the examination of direct effects of classroom practices on I-I and controlling for sub-components of situated interest. Linnenbrink-Garcia and colleagues’ statistical findings suggest that situated interest can develop into I-I.

In contrast, the study by Dohn (2011) was implemented using solely qualitative methods to track the trigging of S-I during a field trip to an aquarium. Four types of data were collected: participant observation of the classroom and field trips, video recording of the entire 10-week period, informal and formal interviews, and photocopies of student work (a biology report due after the aquarium visit). Data were collected in three phases: (1) 8 weeks prior to the aquarium trip (observational data of biology classroom), (2) during the aquarium visit (which lasted the entire day at the end of week 8), and lastly (3) during weeks 9–10 (in-class evaluation of the aquarium tour and follow-up learning activities relating to the trip). Students in the study experienced S-I through the museum’s use of active involvement, novelty and surprise, and social involvement. Findings suggested that teachers can positively influence student interest and learning motivation by selecting educational content that triggers interest and generates positive affect.

Post-hoc analysis proved to be a less costly and less labor-intensive option for Renninger and Bachrach (2015). They examined a previously collected set of data containing thorough descriptions of a summer biology workshop. Interviews were conducted during the first and last weeks of the 5-week program. The authors created a list of triggers based on (1) existing literature addressing interest, collative variables, and affordances; (2) observation records involving group work, social interactions, or hands-on activity; and (3) the cross-referencing of the first and second sources to create a comprehensive list of triggers. The authors repeated steps 1–3 with the new list of triggers. A total of eight triggers of interest were identified within the workshop context: autonomy, challenge, computers/technology, group work, hands-on activity, instructional conversation, novelty, and personal relevance. Notably, the post-hoc analysis was conducted using observational data that were not originally intended to examine interest triggering, and the authors recognize that video data would have been helpful during analysis. The authors also echo the statements found in Dohn (2011) acknowledging that their sample was small and non-random and, thus, may not transfer across groups.

Assessing interest in out-of-school settings using games

Okitika et al. (2015) showcased Polio Eradication (Fig. 1), a life-sized board game, inside of a tent alongside other exhibitions focused on raising global health awareness at the 50th anniversary of the 1962 Seattle World’s Fair. The premise of the game required the collaboration of four players—a researcher, a transportation expert, a local community coordinator, and a healthcare worker—to help contain ongoing and future polio outbreaks in Pakistan.

Fig. 1

Polio Eradication game board depicting a map of Pakistan (Okitika et al. 2015). Players begin at the diamond-shaped square and move along roads (gray) in any direction toward the next town or city. Polio infection spreads through towns (white and yellow squares) or cities (red squares)

Both players and observers who watched one whole game were asked to complete a survey at the end of the game. Random visitors who had not played or observed the game were also invited to take the survey as the comparison group. Game participants were asked to provide a self-assessment on global health knowledge prior to playing or watching the game and on what was learned from the game. Participants were also asked about their current involvement in global health activities and whether the game or other exhibits changed their level of interest in global health. Participants could complete the survey by sitting for an interview with student interns staffing the game or completing the questionnaire on their own.

Okitika and colleagues (2015) used a relative risk regression approach and found three variables to be predictors of increased global health interest: (1) having little or no previous global health knowledge prior to playing the game (risk ratio [RR] = 1.28; 95% confidence interval [CI], 1.13–1.45), (2) not currently being involved in global health (RR = 1.41; 95% CI, 1.07–1.85), and (3) visiting Seattle (RR = 1.25; 95% CI, 1.04–1.51). The author of this paper chose to categorize this study’s interest type as S-I based on the interactivity between the individual (four-player, interactive, hands-on) and the environment (within the context of the global health exhibition). Although the term situational interest was not explicitly referred to, the terms interest, interest in global health, and global health interest were used interchangeably 47 times within six pages. Okitika and colleagues, like Hidi and Renninger (2006), seem to treat interest as something that is emergent, can be triggered, and develops over time.

Pusey and Pusey (2016) implemented MinecraftEdu lessons focused on earth science and coupled these lessons with physical worksheets. The worksheets tracked progression from lesson to lesson and how much activity the student had completed and served as a resource for revising formal assessments (Fig. 2). Data were collected from two-year 8 science classes, one all-girls private school (referred to as Group 1 in Table 1), and a public co-educational school (Group 2) over 5 weeks.

Fig. 2

Models of a plant or animal cell (Pusey and Pusey 2016). All cell functions were required to be labeled with their functions in a signpost

Table 1 Recent assessments of interest using games, by year of publication

Teachers reported an anecdotal increase in student engagement and motivation. A consistent observation at both schools was that a large percentage of students were excited about attending science class, including underachieving students and typically passive students. However, the deliberate use of observational methods was not warranted in the article. A Likert-scale survey was administered to students before and after the program on their use of video games outside of the classroom, whether they had played MinecraftEdu before, their general use of information and communication technologies (ICT), their feelings toward science, and the use of ICTs in education.

Data from student surveys at both schools showed an overall increase in perceptions of ICT and science, with 84% enjoying using MinecraftEdu in the classroom. Group 2 was asked if they would want to use MinecraftEdu in the classroom again, and 94% either agreed or strongly agreed, with only one student out of 29 responding negatively to the question. Negative feedback usually pertained to difficulty in operating the game (having no prior experience playing MinecraftEdu, experiencing a learning curve, having difficulty using a touchpad) or not having complete freedom within the game (having to follow rules and complete worksheets). Those who identified as being interested in earth science increased from 30 to 38%, and most notably, interest in science increased from 47 to 62%. The increase of interest in not only earth science and ICT, but also science as a general topic suggests that games can be an effective way to trigger S-I within the STEM discipline.

Manero et al. (2015) used a game that incarnates the player as the protagonist of the play La Dama Boba (“The Foolish Lady”) to trigger high-school student motivation, and arguably interest, in attending classical theater plays (Fig. 3). Of the students, 94.6% did not know the plot of La Dama Boba prior to the study, 61.9% never went to the theater in the previous year, and 23.6% attended theater only once. Out of the eight schools involved in the study, three were private or charter schools and four were public schools.

Fig. 3

The author of this paper translated this slide as “the game of The Foolish Woman: the characters. From theatre play characters to avatars of a game” (Manero 2013, slide 6)

The study used a mixed experimental design approach, splitting students into two control groups: traditional instruction and traditional instruction with a professional actor playing the male protagonist. The experimental group was assigned to use the game in conjunction with lectures delivered either by a professional actor or by the students’ usual teacher. Every group underwent a pre- and post-test measure consisting of four parts (biographical variables, interest in classic theater, linguistic knowledge, and play knowledge).

Out of a 50-min duration standard for a secondary class in Spain, only five minutes were allocated for the pre- and post-questionnaire, which explains the small number of items (12). The game’s script had to be revised multiple times to fit within the remaining 45-min. On the topic of interest assessment, Manero and colleagues developed a student interest scale measuring interest in classical theater that operated on a three-item, seven-point Likert scale and was calculated by the summation of all values on the scale (i.e., three to 21 points were the minimum and maximum, respectively, that one could score on the scale).

Manero and colleagues used an analysis of covariance to test the effectiveness of each intervention. They found a statistically significant difference (p < 0.05) between game-based instruction and regular teacher-based instruction, ratifying that the game improved student interest in classical theater, student knowledge of linguistic concepts, and student knowledge of the play’s plot more than the regular classroom setting did. However, there was no statistical difference between game-based and traditional instruction for improving student knowledge of linguistic concepts and of the play’s plot (p > 0.05).

The most effective condition was actor-based instruction, which researchers predicted, since the actor’s approach was included as a top-line approach. Actor-based instruction proved more effective than the game approach in improving student knowledge of linguistic concepts and of the play’s plot. The big drawback of actor instruction is its unsustainability, as most schools could not afford to pay a professional actor as an instructor. However, the game was still used in subsequent semesters by multiple schools’ free of cost and without need for maintenance. The work of Manero and colleges is a significant contribution to the literature, as studies that examine the increase of motivation using games are largely focused on STEM disciplines (Mayo 2009; Papastergiou 2009) and not on artistic domains such as opera, music, or painting.

Roure et al. (2015) used Reflex Ridge, one of the top 10 Kinect games in 2015, to examine changes in high-school students’ S-I and physical activity levels during exergame (short for exercise game) play (Fig. 4). Based on interest, 60 participants were recruited to participate, and they were paired off to compete against each other in a one-time 30-min play session. It is unclear why the authors implemented the study near the end of the year, as it prevented the study from being incorporated into the physical education curriculum. Instead, the study was set up in an empty room beside the school library. Accelerometers were used to collect physical activity measures, and participants responded to a S-I scale at the end.

Fig. 4

Kinect Adventures: Reflex Ridge game play (LDS Drive and Entenianick 2010). Players ride on a moving platform resembling a minecart and must maneuver their bodies to jump over hurdles, lean away from articles, and dodge beams. The yellow numbers 90 and 55 denote the number of Adventure pins earned by avoiding obstacles

Results from the authors’ multiple regression analysis showed that 11th grade students spent a significantly higher amount of time in moderate-to-vigorous physical activity than 10th and 12th grade students. The authors found that attention demand emerged as a predictor for moderate-to-vigorous physical activity (ß = 0.41, p < 0.05) and novelty was marginally predictive of light physical activity (ß = 0.25, p < 0.06). In this case, S-I was self-reported using an interest dimension measurement that predicted physical activity levels only. It is unknown why the authors decided to use two-player competitions and 30-min sessions instead of individual play over a longer period.

The work of Roure and colleagues is part of a larger research effort to use games to increase physical activity for K-12 students (refer to Papastergiou 2009, for literature review). A common issue that emerged while the author of this paper searched through articles on education and technology was the lacking quality in several studies, particularly of the research instruments used and justification of research methods and results (a problem within the field previously acknowledged by Angelo et al. 2014, and Mayo2009).

An example of this issue is the study of Zhu and Dragon (2016) regarding a sixth-grade physical education curriculum, a study that was later excluded due to the absence of games. Groups were split between technology use and non-technology use, and all groups completed an S-I scale at the end of each lesson. The experiment group, equipped with scannable QR codes and iPads, measured their heart rates at the end of each lesson, and information regarding their activity levels was available for analysis.

Findings showed that mobile technologies with no direct physical activity prompt had little effect on increasing physical activity or situation interest. What was the purpose of having iPads that show “had no physical activity prompt, merely giving directions/information without requiring little or no physical activity to engage, but instead required cognitive thinking an[d] execution to complete the instructional tasks” (p. 65)? How were the sets of physical activity data meaningful or relevant to participants? It is challenging to predict what researchers had hoped to gain from participants interacting with iPads displaying static information in a physical education curriculum.


Findings from this literature review confirm Renninger and Bachrach’s (2015) claim that most interest measurements are self-reported. In this literature review, five out of seven studies in addition to the work of Zhu and Dragon (2016) rely on self-reporting measures. S-I was the dominant type of interest studied across all articles discussed in this paper thus far (Table 2). The likely explanations for the skew in procedure and type of interest are logistical reasons and an existing gap in the interest literature. The most common sample populations ranged from 6 to 12th grade, suggesting a trend in interest literature applications in real-world settings for adolescents. Outside of research circles and academia, the term interest can be interpreted many ways. What one may describe as interesting, another may label as exciting or weird—simply imagine the conversations at a modern art exhibit.

Table 2 Methods for assessing interest in informal learning settings, by year of publication

Dohn (2011) noted that during interviews, students used the term interest in conjunction with other words that dealt with motivation, liking, fascination, fun, pleasure, and happiness or joy (the author of this paper suspects interest was also used interchangeably with such terms). Dohn suggested this phenomenon as a display of positive attitudes activated through sources of situational interest, but the author of this paper argues that the term interest was too ambiguous and that the researcher should have a narrower definition of interest (for example, specifically looking at interest development in protecting marine life). In future studies, one way to attain clearer responses from respondents of interest, isolated from other constructs, is to provide a working definition of interest at the beginning of the interview. It is advised that those pursuing qualitative interest assessment methods be considerate in the construction of interview questions. For instance, it may be helpful to ask specific questions that isolate motivational variables (e.g., one question about motivation, another on interest of a specific topic or activity, another about willingness to re-engage with a topic or activity).

Findings from this literature review suggest that I-I proves to be more difficult to measure than S-I. The measurement of I-I requires tracking of the same individual(s) across a longer span of time than does S-I and, as a result, would be more cost and time intensive, whereas S-I can be measured by collecting a set of data from a group or groups. Most studies within the game literature measure learning immediately or shortly after playing the game (Wouters and van Oostendorp 2016). Notably, the measurement of I-I would likely involve S-I, but not the other way around. If a researcher wanted to track interest development in biology, instances of S-I (visit to the zoo, watching a nature documentary) are naturally incorporated into the study. However, inclusion of I-I measurements in S-I studies is most suited for case study approaches, which are accompanied by a smaller sample and less generalizability in results, and again would result in more costs and time-intensive efforts from the research team.

A standard measurement of interest development does not yet exist (Renninger and Bachrach 2015). This is problematic and stress inducing when conducting research at institutions operating on separate and fixed schedules, such as 40- to 60-min class periods (cf. Manero et al. 2015). Researchers resort to conducting studies based on volunteers (Roure et al. 2015), but whether the volunteers are offering their time for an incentive (social-related reasons) and/or driven by preexisting interest is out of the researcher’s control. In the case of Manero and colleagues (2015), they could not locate any fully validated instruments that measured interest to fit their particular purpose and target population, and thus, developed their own measurement for interest and motivation. Another method to alleviate the logistical restraints and frustrations that come with interest assessments is to design an intervention around an existing curriculum using existing technologies. Pusey and Pusey (2016) implemented a videogame technology, MinecraftEdu, to assist the teaching of a preexisting earth science curriculum. The game technology was never the focus of the course but served as a supplementary experience that triggered S-I that may lead to I-I in earth science and related topics.

It seems highly beneficial to develop an interest survey that measures interest, engagement, and motivation as separate but coexisting variables and that can be manipulated slightly to suit varying subject areas. In other words, a standard measurement could lead to further insight on interest development (Renninger and Bachrach, 2015) across a range of subjects and disciplines and, on a larger scale, contribute to achieving uniformity in measure within the research literature. It seems that the most promising method of interest assessment, thus, far is the combination of statistical approaches and complementary observational methods, resulting in an in-depth understanding of the interest triggering experience overall.

Data availability

All data generated or analyzed during this study are included in this published article and listed under the references section.


  1. Ainley M, Hidi S, Berndorff D (2002) Interest, learning, and the psychological processes that mediate their relationship. J Educ Psychol 94(3):545–561.

    Article  Google Scholar 

  2. Anderson CA, Bushman BJ (2001) Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: a meta-analytic review of the scientific literature. Psychol Sci 12(5):353–359

    Google Scholar 

  3. Angelo CD, Rutstein D, Harris C, Haertel G, Bernard R, Borokhovski E (2014) Simulations for STEM learning: systematic review and meta-analysis report overview. SRI International, Menlo Park

    Google Scholar 

  4. Arnone MP, Small RV, Chauncey SA, McKenna HP (2011) Curiosity, interest and engagement in technology-pervasive learning environments: a new research agenda. Educ Technol Res Dev 59(2):181–198.

    Article  Google Scholar 

  5. Banks CW, McQuater GV, Hubbard JL (1978) Toward a reconceptualization in the sociocognitive bases of achievement orientations in Blacks. Rev Educ Res 28(3):381–397

    Google Scholar 

  6. Barron BJ (2006) Interest and self-sustained learning as catalysts of development: a learning ecology perspective. Hum Dev 49:193–224.

    Article  Google Scholar 

  7. Boyle EA, Hainey T, Connolly TM, Gray G, Earp J, Ott M et al (2016) An update to the systematic literature review of empirical evidence of the impacts and outcomes of computer games and serious games. Comput Educ 94:178–192.

    Article  Google Scholar 

  8. Chandler CL, Connell JP (1987) Children’s intrinsic, extrinsic and internalized motivation: a developmental study of children’s reasons for liked and disliked behaviours. Br J Dev Psychol 5(4):357–365

    Google Scholar 

  9. Christenson SL, Reschly AL, Wylie C (2012) Epilogue. In: Christenson SL, Reschly AL, Wylie C (eds) Handbook of research on student engagement. Springer, New York, pp 813–817

    Google Scholar 

  10. Connolly TM, Boyle EA, MacArthur E, Hainey T, Boyle JM (2012) A systematic literature review of empirical evidence on computer games and serious games. Comput Educ 59(2):661–686

    Google Scholar 

  11. Cordova DI, Lepper MR (1996) Intrinsic motivation and the process of learning: beneficial effects of contextualization, personalization, and choice. J Educ Psychol 88(4):715–730

    Google Scholar 

  12. Denis G, Jouvelot P (2005) Motivation-driven educational game design: applying best practices to music education. In: Lee N (Gen. Chair), Proceedings of the 2005 ACM SIGCHI international conference on advances in computer entertainment technology (pp. 462–465). New York: Association for Computing Machinery.

  13. Dohn NB (2011) Situational interest of high school students who visit an aquarium. Sci Educ 95(2):337–357.

    Article  Google Scholar 

  14. Dondlinger MJ (2007) Educational video game design: a review of the literature. J Appl Educ Technol 4(1):20–31.

    Article  Google Scholar 

  15. Dweck CS (1986) Motivational processes affecting learning. Am Psychol A1(10):1040–1048

    Google Scholar 

  16. Ell K (2018) Bideo game industry is booming with continued revenue. CNBC.

  17. Evans MA, Norton A, Chang M, Deater-Deckard K, Balci O (2015) Youth and video games. Zeitschrift für Psychologie

  18. Ferguson CJ (2007) Evidence for publication bias in video game violence effects literature: a meta-analytic review. Aggress Violent Beh 12(4):470–482

    Google Scholar 

  19. Furrer C, Skinner E (2003) Sense of relatedness as a factor in children’s academic engagement and performance. J Educ Psychol 95(1):148–162.

    Article  Google Scholar 

  20. Gros B (2007) Digital games in education: the design of games-based learning environments. J Res Technol Educ 40(1):16

    Google Scholar 

  21. Gruber JM, Gelman DB, Ranganath C (2014) States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit. Neuron 84(2):486–496

    Google Scholar 

  22. Hainey T, Connolly TM, Boyle EA, Wilson A, Razak A (2016) A systematic literature review of games-based learning empirical evidence in primary education. Comput Educ 102:202–223

    Google Scholar 

  23. Hamari J, Shernoff DJ, Rowe E, Coller B, Asbell-clarke J, Edwards T (2016) Challenging games help students learn: an empirical study on engagement, flow and immersion in game-based learning. Comput Human Behav 54:170–179.

    Article  Google Scholar 

  24. Harter S (1980) Manual: a scale of intrinsic versus extrinsic orientation in the classroom. University of Denver, Denver

    Google Scholar 

  25. Harter S (1981) A new self-report scale of intrinsic versus extrinsic orientation in the classroom: motivational and informational components. Dev Psychol 17:300–312

    Google Scholar 

  26. Hennessey B, Moran S, Amabile TM (2014) Extrinsic and intrinsic motivation. In: Wiley encyclopedia of management (pp. 1–4). Wiley Online Library

  27. Hidi S (1990) Interest and its contribution as a mental resource for learning. Rev Educ Res 60(4):549–571

    Google Scholar 

  28. Hidi S, Baird W (1988) Strategies for increasing text-based interest and students’ recall of expository texts. Read Res Q 23:465–483

    Google Scholar 

  29. Hidi S, Renninger KA (2006) The four-phase model of interest development. Educ Psychol 41(2):111–127

    Google Scholar 

  30. Hunt J (1965) Intrinsic motivation and its role in psychological development. In: Nebraska symposium on motivation, vol. 13. University of Nebraska Press, pp. 189–282

  31. Isaac JD, Sansone C, Smith JL (1999) Other people as a source of interest in an activity. J Exp Social Psychol 35(3):239–265.

    Article  Google Scholar 

  32. Ito M, Gutiérrez K, Livingstone S, Penuel B, Rhodes J, Salen K et al (2013) Connected learning: an agenda for research and design. Digital Media and Learning Research Hub, Irvine

    Google Scholar 

  33. Kang MJ, Hsu M, Krajbich IM, Loewenstein G, McClure SM, Wang JT, Camerer CF (2009) The wick in the candle of learning: epistemic curiosity activates reward circuitry and enhances memory. Psychol Sci 20:963–973

    Google Scholar 

  34. Kirriemuir J, Mcfarlane A (2004) Literature review in games and learning. A NESTA futurel research report Policy Stud J 3:208.

    Article  Google Scholar 

  35. Krapp A (1999) Interest, motivation and learning: an educational-psychological perspective. Eur J Psychol Educ 14(1):23–40.

    Article  Google Scholar 

  36. Krapp A (2007) An educational–psychological conceptualization of interest. Int J Educ Vocat Guid 7:5–21

    Google Scholar 

  37. LDS Drive and entenianick (2010) Kinect adventures: reflex ridge [Video file].

  38. Lepper MR, Henderlong J (2000) Turning “play” into “work” and “work” into “play”: 25 years of research on intrinsic versus extrinsic motivation. In: Sansone C, Harackiewicz JM (eds) Intrinsic and extrinsic motivation. Academic Press, San Diego, pp 257–307

    Google Scholar 

  39. Lepper MR, Corpus JH, Iyengar SS (2005) Intrinsic and extrinsic motivational orientations in the classroom: age differences and academic correlates. J Educ Psychol 97(2):184–196.

    Article  Google Scholar 

  40. Linnenbrink-Garcia L, Patall EA, Messersmith EE (2013) Antecedents and consequences of situational interest. Br J Educ Psychol 83(4):591–614.

    Article  Google Scholar 

  41. Locke EA, Schattke K (2018) Intrinsic and extrinsic motivation: time for expansion and clarification. Motiv Sci 5(4):277–290.

    Article  Google Scholar 

  42. Manero B (2013) Title of presentation [PowerPoint slides].

  43. Manero B, Torrente J, Serrano A, Martínez-Ortiz I, Fernández-Manjón B (2015) Can educational video games increase high school students' interest in theatre? Comput Educ 87:182–191.

    Article  Google Scholar 

  44. Mayo MJ (2009) Video games: a route to large-scale STEM education? Science 323(5910):79–82

    Google Scholar 

  45. McFarlane A, Sparrowhawk A, Heald Y (2002) Report on the educational use of games. [Online]

  46. Mowrer OH (1938) Preparatory set (expectancy)—a determinant in motivation and learning. Psychol Rev 45(1):62–91

    Google Scholar 

  47. Mowrer OH (1939) A stimulus-response analysis of anxiety and its role as a reinforcing agent. Psychol Rev 46(6):553–565

    Google Scholar 

  48. Nebel S, Schneider S, Rey GD, Journal S, Nebel S, Schneider S, Rey GD (2017) A literature review on the use of Minecraft in education and research mining learning and crafting scientific experiments. Educ Technol Soc 19(2):355–366

    Google Scholar 

  49. Newman RS (1990) Children’s help-seeking in the classroom: the role of motivational factors and attitudes. J Educ Psychol 82(1):71

    Google Scholar 

  50. Lamborn S, Newmann F, Wehlage G (1992) The significance and sources of student engagement. Student engagement and achievement in American secondary schools 11–39

  51. Okitika TA, Barnabas RV, Rue T, Weisman J, Harris NA, Orenstein WA, Wasserheit JN (2015) “Polio eradication” game may increase public interest in global health. Games Health J 4(3):195–201

    Google Scholar 

  52. Papastergiou M (2009) Digital game-based learning in high school computer science education: impact on educational effectiveness and student motivation. Comput Educ 52(1):1–12

    Google Scholar 

  53. Prensky M (2001) Digital game-based learning. McGraw-Hill, New York

    Google Scholar 

  54. Pusey M, Pusey G (2016) Using Minecraft in the science classroom. Int J Innov Sci Math Educ (formerly CAL-laborate International) 23(3)

  55. Qian M, Clark KR (2016) Game-based learning and 21st century skills: a review of Renninger, K. A., & Bachrach, J. E. (2015). Studying triggers for interest and engagement using observational methods. Educ Psychol 50(1):58–69.

    Article  Google Scholar 

  56. Renninger KA, Hidi S (2011) Revisiting the conceptualization, measurement, and generation of interest. Educ Psychol 46(3):168–184

    Google Scholar 

  57. Renninger A, Bachrach JE (2015) Studying Triggers for Interest and Engagement Using Observational Methods. Educ Psychol 50(1):58–69.

    Article  Google Scholar 

  58. Reschly AL, Christenson SL (2012) Jingle, jangle, and conceptual haziness: evolution and future directions of the engagement construct. In: Christenson SL, Reschly AL, Wylie C (eds) Handbook of research on student engagement. Springer, New York, pp 3–19

    Google Scholar 

  59. Roure C, Pasco D, Pope Z, Gao Z (2015) High school students’ situational interest and physical activity levels in exergaming. In: La revue nouvelle

  60. Ryan RM, Deci EL (2000) Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemp Educ Psychol 25(1):54–67.

    Article  Google Scholar 

  61. Sadoski M, Goetz ET, Rodriguez M (2000) Engaging texts: effects of concreteness on comprehensibility, interest, and recall in four text types. J Educ Psychol 92(1):85

    Google Scholar 

  62. Schiefele U (1991) Interest, learning, and motivation. Educ Psychol 26(3 & 4):299–323

    Google Scholar 

  63. Schiefele U, Krapp A (1996) Topic interest and free recall of expository text. Learn Individ Differ 8(2):141–160

    Google Scholar 

  64. Schraw G, Lehman S (2001) Situational interest: a review of the literature and directions for future research. Educ Psychol Rev 13(1):23–53

    Google Scholar 

  65. Schraw G, Bruning R, Svoboda C (1995) Sources of situational interest. J Read Behav 27(1):1–17

    Google Scholar 

  66. Singh K, Granville M, Dika S (2002) Mathematics and science achievement: effects of motivation, interest, and academic engagement. J Educ Res 95(6):323–332.

    Article  Google Scholar 

  67. Skinner BF (1948) ’Superstition’in the pigeon. J Exp Psychol 38(2):168

    Google Scholar 

  68. Thoman DB, Smith JL, Silvia PJ (2011) The resource replenishment function of interest. Social Psychol Pers Sci 2(6):592–599.

    Article  Google Scholar 

  69. Thorndike EL (1911) Animal intelligence: experimental studies. Macmillan, New York

    Google Scholar 

  70. Thorndike EL (1927) The law of effect. Am J Psychol 39(1/4):212–222

  71. Trotter A (1992) Technology in classrooms:" that's edutainment!". Educ Digest 57(5):2

  72. Tyler-Wood T, Knezek G, Christensen R (2010) Instruments for assessing interest in STEM content and careers. J Technol Teach Educ 18(2):341–363

    Google Scholar 

  73. Tzuriel D (1989) Development of motivational and cognitive-informational orientations from third to ninth grades. J Appl Dev Psychol 10(1):107–121

    Google Scholar 

  74. Vallerand RJ, Ratelle CF (2002) Intrinsic and extrinsic motivation: a hierarchical model. Handbook of Self-Determination Research 128:37–63

    Google Scholar 

  75. Van Eck R (2006) Digital game-based learning: it's not just the digital natives who are restless. Educause Review 41(2)

  76. Wang Z, Adesope O (2016) Exploring the effects of seductive details with the 4-phase model of interest. Learn Motiv 55:65–77

    Google Scholar 

  77. Well AD, Myers JL (2003) Research design & statistical analysis. Psychology Press

  78. White RW (1959) Motivation reconsidered: the concept of competence. Psychol Rev 66(5):297

    Google Scholar 

  79. Wouters P, van Oostendorp H (2016) Overview of instructional techniques to facilitate learning and motivation of serious games. Instructional Techniques to Facilitate Learning and Motivation of Serious Games.

    Article  Google Scholar 

  80. Zhu X, Dragon LA (2016) Physical activity and situational interest in mobile technology integrated physical education: a preliminary study. Acta Gymnica 46(2):59–67.

    Article  Google Scholar 

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This material is based upon work supported by the National Science Foundation under Grant No. 1713609. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Yi, S. Playful learning in the twenty-first century: Motivational variables, interest assessment, and games. SN Soc Sci 1, 151 (2021).

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