Learning Inside the School, but Outside the Curriculum: An Extreme Case of Interest-Driven Learning in Alternative STEAM Learning Infrastructure for Schools

Abstract

Choice and autonomy are central tenets of interest-driven learning. Yet, in most studies on interest in school, students’ choice and autonomy have been confined within the boundaries of the curriculum and the subject matter in question. This limits our understanding of how schools can support interest-driven learning as well as students’ interest development in educational settings more broadly. To address this gap, in this study, we have focused on student learning when they are allowed to follow their interests beyond the curriculum during school time. Building on relational and practice-based perspectives on interest, we conceptualized such extensions as productive deviations and centered on a particular case of two 6^th-grade students - Tamaz and Nuri - who created two computer games during their time in the FUSE Studio, alternative STEAM learning infrastructure for schools. Our interactional analysis of Tamaz and Nuri’s problem-solving during their game-making shows that their productive deviation formed a significant learning experience for them in terms of game design and working with computers. Overall, our study contributes to discussions on fostering and supporting students’ interest-driven learning and interest development in school settings.

Keywords:

• Interest
• agency
• learning
• ethnography
• STEAM
• school

Introduction

The mind is not a vessel to be filled, but a fire to be kindled.

Plutarch (1927)

This study focuses on a less-researched aspect of interest in school, namely student learning, when student interests extend and lead them beyond the curriculum. Building on previous work (Azevedo, 2006; Rajala & Sannino, 2015), we conceptualize these extensions as productive deviations¹ (Hilppö & Stevens, 2023), activities created and introduced to the classroom by students, and which become recognized as legitimate by the classroom community. Although existing research shows that interest can be a powerful motivator for learning both in and outside school (Azevedo, 2013; Barron, 2006; Hidi & Renninger, 2006; Renninger et al., 2015) and that students’ diverging interests can fuel curricular goals rather than jeopardize them (Azevedo, 2006), empirical analyses of student learning when their interests extend beyond the curriculum in school settings are few. This is largely due to the under-conceptualization of student agency, specifically its transformative aspect, in studies on interest in school, and this impacts our understanding of how students’ interest-driven learning could be supported. Below, we elaborate on these limitations and how we have addressed them in this study.

Choice and autonomy are central tenets of interest-driven learning (Hidi & Renninger, 2006; Renninger et al., 2019). Yet, in most studies about interest in school, students’ choice and autonomy have been conceptually confined within the boundaries of the curriculum and the subject matter in question. Dorfner et al. (2018) recent work on instructional quality and students’ situational interest is a good example. In their study, Dorfner and colleagues collected video records from regular secondary school biology lessons and analyzed their instructional quality in terms of classroom management, supportive climate, and cognitive activation in each lesson. Dorfner et al. then combined these observations with the students’ self-reports on how interesting each lesson and the lesson topic had been to them. While their study convincingly showed that quality instruction supports student situational interest, their analytical framework focused on student and teacher actions and self-reports on interest only from the perspective of the assigned biology curriculum. That is, actions that might have extended beyond the curriculum, like students’ formulating and pursuing interest-driven goals sparked by but not directly assigned within the curriculum, were beyond the conceptual and analytical focus of this study.

This under-conceptualization can be partly explained by the structural rigidity of schools in relation to students’ interests. Existing studies show that institutional arrangements, like curricular objectives and materials, timetables, and the division of labor between teachers, significantly constrain teachers’ options for accommodating and supporting students’ interest-driven engagement when it extends beyond the curriculum (e.g., Anderhag et al., 2016; Birbili, 2018). For example, analysis of students’ task interpretation by Rajala and Sannino (2015; see also Rajala et al., 2016) showed that students’ frequent attempts to modify the teacher-given tasks were impeded by the overall structure of the school activity. Furthermore, the students’ interests focused on peripheral aspects of the task from the teacher’s perspective (Rajala & Sannino, 2015). Accommodating the students’ diverging interests, although possible (see Pressick-Kilborn, 2015), would have meant rearranging the activity completely. Maltese and Harsh (2015) pointed out that the underlying issue rests with the idiosyncratic nature of interest development. Identifying good instructional practices, curricula, or interventions to spark and support interests is hard for teachers when these interests diverge and change too quickly for the schools’ organizational timescale.

To address these limitations, in previous studies we focused on students’ interest-driven engagement in an in-school learning environment—the FUSE Studio classroom—in which the aforementioned constraints are largely absent. FUSE Studios are an alternative learning infrastructure for schools (Stevens et al., 2016) in which students choose among about 30 challenge sequences designed to support and develop their interests in science, technology, engineering, arts, and mathematics (i.e., STEAM). Importantly, in addition to students being allowed to self-select and self-pace their progress through the challenges, students are also allowed to build on, combine, and transform the challenges based on their interests. In our previous work, we conceptualized these extensions as productive deviations (Hilppö & Stevens, 2023), and drawing on our year-long ethnography of seven FUSE Studio implementations, we showed that they are a common feature of FUSE Studios and can range from short excursions to semester-long projects. We also found that in addition to students’ interests, the emergence and extent of the productive deviations could be accounted for by the support of the social and material infrastructure of the FUSE Studios. That is, students were trusted by the adults in the classroom, and other students showed their interest in the deviation, even to the extent of joining the deviation themselves, which in turn spurred the deviation even further.

While illuminating, our previous studies on productive deviations (or similar studies like that by Azevedo, 2006) did not explore what students learned during or through them. To this end, in this study, we focused on a case of two students, Tamaz and Nuri (all participant names are pseudonyms), who followed their interest in video game design and went beyond what FUSE challenges guided them to do to create two video games of their own. For us, understanding the learning potential that cases like Tamaz and Nuri’s game-making entail offers empirical substance to questions about student interests and interest development in schools (e.g., Anderhag et al., 2016; Birbili & Hedges, 2019; Renninger et al., 2015). As researchers and educators, if we want to design and support educational environments in which our students’ interests are kindled in the spirit of Plutarch’s metaphor we need to understand better what students learn when they are allowed to venture beyond the curriculum and how they put into play what they have previously learned when doing this.

Our article proceeds as follows. In the next section, we will elaborate on the theoretical framework of our study. In short, we will explain how i) interests are relational and practice-based (Azevedo, 2011; Dewey, 1913); ii) people demonstrate agency in relation to their interests and create new opportunities to pursue them (Rainio, 2008; Sewell, 1992); and as a result, iii) new opportunities for learning emerge when such interests are pursued (Dewey, 1910; Schraube et al., 2013). We will then describe the methods we used to study students’ interest-driven learning during productive deviations and share the results of our analysis of Tamaz and Nuri’s game-making. We concluded the article with a discussion of these results and their relevance for understanding and supporting student interests and interest development in schools.

Interest, learning, and agency: a theoretical framework

For this study, we conceptualized interest as a dynamic goal-oriented process of engagement between a person and their object of interest (Azevedo, 2011; Dewey, 1913). Metaphorically, such processes have been described as pathways or lines that the interested person creates in and across different settings (Azevedo, 2011; Cole, 1998; Ingold, 2007; Nasir et al., 2020; Stevens et al., 2008b). Accordingly, the psychological features that often characterize interest as a phenomenon, like attuned concentration and positive emotions, are understood holistically as being related to a particular object. Importantly, objects in this sense cannot be reduced to a generalized topic; rather, they are also constituted by the various communities connected to it and their social and material arrangements (Azevedo, 2011).

This relation between a person and their object of interest develops through engagement (e.g., Hidi & Renninger, 2006). Initially, the not-yet-interesting object has no specific motivational pull when introduced to the person, for example, as part of a happenstance discussion or classroom activity. As the discussion or activity continues, the object starts to appear as something enticing and pursuable by the person, and their interest is sparked. Which aspects of the not-yet-interesting object spark this interest depends on personal tastes and the activity engaged in Anderhag et al. (2016). When these initial interests are pursued, the object reveals new aspects of itself. These new aspects can entice further engagement and eventually become part of what fuels the relationship between the person and their object of interest. In this sense, pursuing one’s interest can be characterized as a process of exploration, adventuring into the interest as an open-ended pursuit. While specific goals might be realized through engagement, at the same time, new goals and opportunities also appear and are explored.

Learning is a vital part of this exploration, especially how various problems emerging during the pursuit of one’s interest are dealt with. Following Dewey (1910; see also Koschmann et al., 1998; Miettinen, 2000; Stevens & Hall, 1998), we understand that learning is often, but not always, initiated when a habitual way of doing things is disrupted or breaks down. Resolving the yet-unknown source of the breakdown begins with problem inspection. After this, a working hypothesis is first formulated and tested. If the tentative solution does not work, the process of exploring the problem is continued with knowledge gained from the first attempt. When the problem is solved, the person moves forward with their pursuit, and the experience of resolving the issue turns into a resource for future problem-solving. Moreover, encountering, grappling with, and possibly solving problems when pursuing one’s interest can also impact how the interest and the problem are perceived together. As Holzkamp argues (Schraube et al., 2013, p. 125), a problem-solving process can generate an expansive change in the perspective of the problem solver, a reflective overview and re-focus of the object of one’s interest and the problem at hand. This underscores the fundamental openness and inquiry nature of the learning process.

Importantly, learning through problem-solving in this sense should not be taken as solely a process of acquiring knowledge or developing more accurate cognitive representations of the object. Rather, for us, learning is marked by having the competence to work with reality in increasingly complex and multiple ways and generating “habits of action for coping with reality” (Rorty, 1991, p. 1). Over time, such learning can result in habitual practices and associated learning ecologies rich in ways to engage with and develop one’s interests, as Azevedo’s (e.g., 2011) and Barron’s (2006) studies have shown.

Social and material arrangements are important for how interests can be scaffolded (e.g., DiGiacomo et al., 2020; Pressick-Kilborn, 2015; Valsiner, 1992). In addition to sparking one’s interest, different social and material arrangements can also help maintain and channel these interests further, such as when parents engage with their child’s interest in trains by going to museums together (Hedges, 2019; Crowley et al., 2015). These arrangements can also have a degrading impact on interest development. Lack of educational or other resources in one’s neighborhood or misalignment between a student’s interest and the designed curriculum can affect how interests are followed, if at all (e.g., Anderhag et al., 2016; Chesworth, 2019; Warrington, 2005). In line with the previous metaphors, classroom and family practices are on-ramps and roads that support pursuing one’s interests or, alternatively, obstacles that impede it.

However, these practices do not solely determine how people engage with their interests. Rather, people have agency (e.g., Sewell, 1992), and they can create new ways to follow their interests. These new ways stem from the continued engagement with and learning about the object of interest. That is, through engagement and learning the person’s understanding of how various practices both afford and limit their engagement with their interest, their sense of agency grows. This sense forms the basis of transformative agency (e.g., Rainio, 2008), actions by which students change teacher-given tasks to meet their interests and start to deviate from the tasks. As discussed, the extent to which these transformations can be accommodated in school (or other educational settings) depends on how aligned they are with the existing practices and how productive or not they seem to the other participants in relation to the goals of the practice (Azevedo, 2006; Rajala & Sannino, 2015; Stevens et al., 2016).

In our previous work, we have conceptualized such transformations as productive deviations (Hilppö & Stevens, 2023). In short, productive deviations are activities created and introduced to the classroom by the students that deviate from teacher-created ones and from students’ actions instructed by the curriculum materials. In turn, these deviations can become recognized as productive and therefore legitimate by the teacher and other students. In effect, following the deviations leads the students outside the designed pedagogical support structures and scaffolds created by the curriculum and the teacher. In practice, these deviations can range from alterations to given instructions (using alternative materials or tools or skipping a step) or changing the goal of the task. This can mean that while engaging with the deviation, the students encounter and need to solve more complex problems regarding their interest than before. Moreover, pursuing the deviation also means students shoulder more responsibility for sustaining the activity. That is, depending on the deviation, teachers might not be able to guide the students to relevant knowledge sources, or the classroom might not have the materials needed, and students might need to produce these by themselves.

Materials and methods

To understand students’ interest-driven learning that goes beyond the curriculum, we analyzed video ethnographic data collected from seven FUSE Studio implementations in three schools located in a large Midwestern school district in the US during the 2015–2016 school year. We will next describe the FUSE Studio model, its activities, and the key design principle of student choice. After this, we will describe the implementation of the model across the seven studios, especially typical FUSE Studio practices and student accountability during the FUSE Studio sessions.

The FUSE studio model

The FUSE Studio is a model for an alternative form of learning infrastructure in school (Stevens et al., 2016). Its main goal is to support students in discovering and developing new interests or further developing existing interests brought from out-of-school pursuits. The model is also designed to develop students’ collaboration skills, creativity, critical thinking, and other related competencies associated with the broad notion of 21^st-century skills.

The core activities of the FUSE Studio model revolve around a suite of about 30 STEAM (science, technology, engineering, arts, and mathematics) challenges. These challenges range from building solar cars, laser mazes, and roller coasters to designing and printing 3D jewelry, coding video games, and designing houses with 3D modeling software. Some of the challenges are completely digital, while others require students to use tangible materials provided to them in kits. The students access the challenges through a website (Figure 1). The challenges are arranged in sequences that ‘level up’ like video games (Figure 2). To complete a challenge, the students work step-by-step on an artifact that they design and create (e.g., a 3D-printed keychain or a ringtone for their phone). The FUSE website offers the students help resources in the form of video tutorials, images, and links to other websites to support the completion of their challenge. Unlocking the next level happens by uploading a digital artifact (e.g., a picture, a video, or a file) that demonstrates the completion of the previous challenge. The next level is designed to be more difficult or complex and builds on the skills that were needed in the previous level in the sequence.

Figure 1. FUSE Studio website.

Figure 2. FUSE Studio challenge sequences.

To support students’ interest discovery and development, the FUSE Studio model is built around the principle of student choice. In the FUSE Studio, students are allowed to choose which of the challenges they want to work on, the pace they work at, when to stop working on a challenge, and whether to work alone or with others. After starting a challenge that has sparked their interest, they can either keep working on the level as long as they want to, progress to the next level, or stop working on it and start a different challenge (Figure 3). The students are also allowed to restart any challenge or level they have already done and re-do it, which many students do. To support students’ interest-driven engagement further, students are not formally assessed or graded on their challenge completion in the FUSE Studio model. Instead, teachers, who are called facilitators in the FUSE Studio, to emphasize their role in helping students discover what interests them, are encouraged to follow their students’ work and to be interested in how their students are progressing with the challenge and keeping the students engaged with support and encouragement. Overall, the principle of student choice, coupled with the challenge design and the lack of formal assessment structure, allows the students to exercise a high degree of agency over their work and their ways of working in the FUSE Studio.

Figure 3. FUSE Studio user experience.

Implementation of the FUSE Studio model

At the three schools at which this study took place, the FUSE Studio model was implemented as a science enrichment class for all 5^th and 6^th graders and was part of their science curriculum. The students worked in the FUSE Studio for 90 minutes per week for the whole year, with the homeroom teacher acting as the facilitator. By the time of our data collection, the schools had been running their FUSE Studios for a year, meaning that the 6^th graders in each studio were familiar with FUSE and the challenges. For the 5^th graders, the goals of the studio work were presented at the start of the year as engaging with the STEAM disciplines in the form of challenges, problem-solving, persistence, helping others and having fun while doing it. In a similar fashion, if a new student joined the studio during the year, FUSE was introduced as being about “doing challenges” and “doing something you want to work on.” We also learned that the students would receive a pass/fail grade for their work in the FUSE Studio. None of the studios had challenge completion requirements or other formal assessment practices regarding student grading. Should they choose to do so, the students could work on a single challenge for the whole year without completing it and receive a passing grade. As an exception, in the spring period, one studio required the students to complete one challenge per month, to foster 6^th graders’ challenge engagement. However, this requirement was not enforced because its introduction had already spurred new and sustained challenge engagement. Overall, across the studios, we observed that most students engaged with and completed multiple challenges and challenge sequences over the year, while some focused on one or two particular ones (e.g., Hilppö & Stevens, 2023; Ramey & Stevens, 2019).

Across the seven studios we observed, the FUSE Studio model was implemented in a way that created a palpably different learning culture and accountability structure from traditional subject matter classrooms. Aligned with the principle of student choice, during FUSE Studio sessions, the students selected which challenges they would work on, self-paced their work, and could change the challenge during the session. The students were also allowed to change from working on a challenge by themselves to working with a pair or larger group of students. This meant that at any given moment, there would be several challenges being worked on at the same time in the studio, and students could freely move around the class between groups, the cabinets where the challenge materials were, and the 3D printer (Figure 4). During a FUSE Studio session, students were allowed to move around the room, stop to observe what others were doing, and engage them in discussion. Students would also often talk together while working on adjacent computers, either doing the same challenge individually or doing separate challenges. In addition to talking about what they were doing, students would also talk about other things, like other schoolwork or their lives outside school. This meant that the soundscape of a FUSE Studio was busy with chatter between students, the sound of the 3D printer working, instructional videos playing from the FUSE website, and ringtones being composed.

Figure 4. Long shot of a typical FUSE Studio session.

While the students were engaged with the challenges, the facilitator would circle the room, observe the students’ work, drop in comments or questions about their progress, and help when asked. Routinely, the students would also ask for help from their peers during studio time. A common feature across the studios was that students who were further along in the levels of a given challenge would become relative experts (Stevens et al., 2016) in their studio regarding that challenge and be expected to help others. The facilitators would often direct help-seekers to turn to the relative experts in the room and even ask for their help. If the room was running smoothly, the facilitators would occasionally also work on other non-FUSE related things (e.g., emails, grading, etc.) but still be available for the students and monitor the activities in the room. Likewise, the students would also occasionally engage in things other than the challenges, such as playing online games or socializing for longer periods, just as adults at work often do. The facilitators had a range of responses to this. Some allowed it more and permitted students to take breaks from the challenges. In comparison, other facilitators would more quickly usher students to either continue with the challenge they were working on or to pick a new one, often by asking if what they were doing related to a challenge or not. Students would respond either by resuming with the challenge they had been doing or explaining how their current engagement was related to the challenge. Overall, these facilitator interventions were rare because the students predominantly kept themselves engaged with the challenges from the start of the studio sessions to their end.

Data collection

The focus of our ethnographic study was on understanding the students’ and the facilitators’ experiences in the FUSE Studio, their learning, and the development of the studio culture during the year. To this end, we collected data from each studio in the following ways. At the beginning of each studio session, we asked seven students to wear a visor camera, an action camera attached to a visor cap, to follow their activities from their perspectives. To ensure that the students were comfortable in wearing the visors and sharing their work with us, wearing the visors was optional, and the students could say no when asked if they wanted to wear the visors even if they and their parents had already consented to participate in research. In practice, many students were eager to wear the camera throughout the year, while others wore it occasionally, and some declined altogether. Regarding productive deviations, if we had seen a student engaging with what might be a productive deviation during a FUSE Studio session, we would ask the student to wear the visor during the next session. We also placed a video camera at the back of the studio to record a long shot of the activities in the room. In addition, we collected field notes, conducted impromptu interviews, and took photographs of artifacts created during the sessions. We also collected a weblog of the students’ use of the FUSE Studio website, which recorded their logins to the site, which challenges they had started, completed, or quit a challenge, and whether they had indicated having collaborated with other students when working. At the end of the year, we conducted semi-structured interviews with the facilitators and students we had substantial visor camera material from, and who had agreed to be interviewed. We wished to understand their experiences over the year from their perspectives. As part of the interview, we also asked the students to reflect on what they had learned in FUSE during that year.

Analysis

Our analysis proceeded in two phases. The first phase began with us first compiling a list of all the productive deviations we had observed during the year. In practice, we identified situations from our ethnographic materials in which the students had been working on the challenges in ways that were not aligned with the instructions and used the challenge materials or software to do something else. We identified 15 deviations. Next, we constructed person-centered ethnographic accounts (Stevens et al., 2008a) of these cases, which outlined the challenges the students worked on during the year and how their work progressed during the sessions. We used the students’ visor camera video, webdata, our field notes, other students’ visor material, and the long shot footage to construct these accounts. Following interaction analysis methods (Hall & Stevens, 2016; Jordan & Henderson, 1995; Stevens, 2020; Stevens & Hall, 1998), we then created more detailed ethnographic descriptions of the periods when the students had been working on the productive deviations. This phase entailed identifying when and how the deviation had started, who worked on the deviation during the process, how the work had progressed, and how it had ended. We also detailed how other students, the facilitator, or other visiting adults reacted to the deviation over time. We also read through the end-of-the-year interviews and identified episodes in which the students and facilitators talked about the productive deviations and their experiences of them. Lastly, to understand the differences and similarities between the productive deviations we had identified, we compared our analysis of each deviation against each other. As a result, we observed that these deviations ranged from small alterations to the FUSE challenges to more considerable departures during which the students introduced new tools and activities to their studio (for detailed analysis of all deviations, see Hilppö & Stevens, 2023).

In the second phase of analysis, we selected one particularly extended deviation for closer analysis as a case study. In the deviation in question, two boys, Tamaz and Nuri, spent more than half their scheduled time in FUSE that year (34 studio sessions, ∼22.5 hours in total) creating two computer games of their own. Compared to the other deviations in our data, Tamaz and Nuri’s case could be characterized as an extreme case (Patton, 1990) both in relation to the time spent on the deviation, as well as the way in which making the games seemed to go well beyond the structured support of the challenge that had inspired Tamaz and Nuri. In his end-of-the-year interview, Tamaz also spoke about this. When asked about what he had learned over the year in FUSE, he gave us the following answer:

I definitely learned a lot about computer science. I’ve been using one every day so now I can look through computer files and understand everything rather than having it seem like gibberish. I obviously learned a lot more about the softwares they use, which is useful because I found the softwares really fun to use, and I can create a lot of things with it, so I like to use them at home sometimes. I learned how to be creative and be a problem solver because there are a lot of problems I encountered over the year. All of them I had to find my own solution to because the FUSE website didn’t always have a guide to it.

Tamaz, interview 2016-05-09

In addition to highlighting three connected things that he learned in FUSE (i.e., to work with computers, to be creative, and to solve problems), his last comment emphasizes that, at times, he needed to go beyond the FUSE website and create solutions to the problems he faced by himself. Based on our initial observations of Tamaz’s and Nuri’s game-making and Tamaz’s perspective on his learning experiences in FUSE, we chose this case as an exemplar for understanding learning during productive deviations.

We proceeded next to analyze the case material regarding game-making with a particular focus on what problems Tamaz and Nuri encountered and how they solved them. In practice, this meant that we identified moments from our data in which Tamaz and Nuri’s game-making was disrupted or stopped by an issue that neither of them immediately knew how to handle and which needed to be addressed somehow before they could proceed with their game-making. In addition, we identified moments when they discussed a problem they had encountered at other times (e.g., playing their game at home or when not wearing the visor camera). This resulted in 24 episodes, ranging from two to 25 minutes per episode (totaling two hours and 46 minutes). We then focused on how Tamaz and Nuri solved the problems or reflected on them and, through constant comparison, sought to identify differences and similarities in the process across the episodes. In addition, if the problem was not solved during the episode in question, we then checked the subsequent videos, field notes, and the games themselves to determine how, if at all, Tamaz and Nuri had solved the issue.

In addition, we traced Tamaz and Nuri’s creative process with both games step-by-step to understand the games’ design elements and how Tamaz and Nuri created them. For example, we followed how the various levels were created, what actor behaviors Tamaz and Nuri incorporated into both games, and what tools and other resources they used in creating them. In this, we specifically focused on which design elements could be explained by what Tamaz and Nuri had learned from the challenge and which features had required them to learn something that was not part of the challenge. We also followed Tamaz and Nuri’s reflections between themselves and others about their games to understand their perspective on their making process.

Overall, to understand Tamaz and Nuri’s learning during their productive deviation, we focused on what problems they encountered, how they solved them, and what they had learned about game-making that was not covered by the available challenge materials. Our process was guided by the following research questions:

• What problems did Tamaz and Nuri encounter when making their games, and how did they solve them, if at all?

• How did Tamaz and Nuri use what they had learned from the challenge when making their games, and what new actions did Tamaz and Nuri engage in?

Results

In this section, we present the results of our analysis in the order of our research questions. However, to contextualize them, we have provided a narrative description of how Tamaz and Nuri’s game-making proceeded during their FUSE Studio sessions, the two games they created, and the challenge they worked on before starting their productive deviation.

Tamaz and Nuri, making “SMASH” and “Mario and Luigi”

Tamaz’s and Nuri’s game-making started in late January (see Figure 5). Prior to this, they had been working on a FUSE challenge called Game Designer, which had been released in their studio in December. In Game Designer, the students are invited to fix and enhance a Super Mario-style platform game with Stencyl, a game creation software. Following the FUSE challenge structure, each of the four levels introduces progressively more challenging tasks to the students. They start by changing one aspect of a game character’s actions, Mario’s jump force on the first level, and then design a new scene and alter its physics. The help tutorials on the different levels guide the students in changing level design and characteristics (like the direction and force of gravity), adding new actors (e.g., collectible coins), and changing actor behaviors (e.g., having Mario shoot fireballs). Tamaz and Nuri were among the first in their studio to complete all the levels of the challenge, partly because they also self-selected to work on the challenge at home. When working on the last level of the challenge, Tamaz told Mr. Lindblom, a visiting facilitator who had commented positively on Tamaz’s programming skills, that he had no prior experience with programming and attributed his programming learning to the challenge tutorials. Tamaz also explained that he did not originally think that programming video games would be as hard as he had found it to be. During the same session, Tamaz also explained that: “After level four I’m gonna use what I’ve learned and put a little twist in the game.”

Figure 5. Tamaz and Nuri’s challenge and deviation engagement timeline.

What this twist meant in practice was “making a game from scratch,” as Tamaz worded it at the beginning of their next FUSE Studio session. When asked why, Tamaz and Nuri explained that all the tiles and characters had already been chosen for them in the FUSE challenge, and they wanted to have more creative control. However, coding and animating all characters and levels for their game by themselves would require a lot of time and effort. Instead, Tamaz and Nuri chose to use ready-made material created and shared by other Stencyl users via StencylForge, an online repository of game-making resources like actor animations and behaviors and user-created games. Tamaz and Nuri could access these resources directly through Stencyl but needed to tailor them to fit their purposes.

Over the next nine FUSE Studio sessions, Tamaz and Nuri created their first game, entitled SMASH. SMASH was a “fighting game,” according to Tamaz, made in homage to the commercial game Super Smash Bros that inspired them. The game has four levels, each named after its main design feature (e.g., the “Trapdoor” level has trapdoors through which the characters can fall). The objective of the game was to defeat the other player by pushing them off the stage. After this, the players transition to the start page (Figure 6) and can select a different level to fight in. While making their first game, Tamaz and Nuri became recognized as the go-to people, or relative experts (Stevens et al., 2016), of their studio regarding Stencyl. Other students in their studio came to them to ask Tamaz and Nuri’s help with Game Designer challenges and working with Stencyl. The other students also sat in with Tamaz and Nuri and observed their game-making, and Mrs. Klein, the facilitator of their studio, wrote with appreciation about Tamaz’s and Nuri’s game-making in their classroom newsletter in February.

Figure 6. SMASH start screen.

While working on SMASH, Tamaz and Nuri got an idea for their second game. At the end of their seventh session working on SMASH, when waiting to leave for their next scheduled class, Tamaz said to Nuri, “We should just do a two-player side scroller², you know what I mean?” Nuri did not take to the idea at first, but a moment later continued with Tamaz’s idea and suggested, “We should just do a regular Mario game. I’m gonna be Luigi and you will be Mario.” Three FUSE Studio sessions later, they had finished working on SMASH and started to work on their new game “Mario and Luigi.” Tamaz and Nuri worked on Mario and Luigi for the rest of the semester, from mid-February to the end of May, for 25 FUSE sessions.

“Mario and Luigi” was also a platform game, but unlike SMASH, the goal of the game was cooperative. The players would work together to get to a flag at the end of a level that would transfer them to the next stage. As a gaming experience, Tamaz and Nuri’s design of “Mario and Luigi” was much more extensive (see Figure 7). The game consisted of 24 levels divided into specific worlds and boss levels. As with SMASH, each level had its defining design idea, but they were much more elaborate and took more time to play. In contrast, each boss level consisted of a single screen with only the boss whom the players had to defeat. The game ended with a level that featured all the design ideas of the previous levels in sequence and ended with battling all the bosses together. An important moment in the making of “Mario and Luigi” took place at the beginning of March, during the seventh session of making the second game. While Tamaz was working on the second stage of World 1, Nuri asked Tamaz to stop working, pulled up the Post-It note they had used to track their design ideas, and said, “I wanna make it like our own worlds instead of like actual worlds.” Up to this point, their reference for level designs had been grounded in existing Mario game level designs. Tamaz agreed with Nuri’s suggestion, and they proceeded to base their level designs on the tile sets available to them. During the spring term, Tamaz and Nuri uploaded both of their games to StencylForge. The upload made their games available to their peers in the FUSE Studio and to the larger community of StencylForge users, roughly 400,000 game makers at the time. By the end of the school year, “SMASH” had been downloaded 113 times and “Mario and Luigi” 44 times.

Figure 7. A visor cam screenshot of all levels in Mario and Luigi.

Throughout their productive deviation, Tamaz and Nuri worked collaboratively. In practice, they divided the work by taking turns at designing one level at a time. While the other was working on the level, the other one would observe and pitch in with suggestions or occasionally use another computer to look up ideas. Although Tamaz and Nuri sometimes disagreed and argued about their games, their interactions were dominantly amicable. They worked mostly by themselves but were occasionally joined by other students interested in their game-making. These students would observe them working, pitch in with ideas, or test their game by playing it for a while. Additionally, they also came to Tamaz and Nuri for help with Game Designer or Stencyl. The studio facilitator, Mrs. Klein, interacted with Tamaz and Nuri only a few times at the start of their deviation. These interactions focused mainly on one of the computers Tamaz and Nuri were trying to use, which was not working properly. Although Mrs. Klein largely remained away from Tamaz and Nuri’s game-making, she was aware and appreciative of what they were doing. This is evident from the following quote from her end-of-the-year interview in which she reflected on students who stood out for her during the year. “I guess the stories with Tamaz and Nuri. You know, they’re trying to figure out what to go beyond. Just that, putting that game together and really enjoying it and really kind of digging deep into that and then even just their partnership and working together with that, and then problem-solving through that.” When compared to other facilitators’ reactions to and interactions with productive deviations in their FUSE Studios or the two deviations in her own studio, Mrs. Klein’s facilitation was not significantly different. What was notable is that with one of the other deviations in her own studio, she once intervened more. In short, she denied a student permission to 3D print a knuckle duster (i.e., “brass” knuckles) the student had designed and justified this to the student by referring to the school’s policy on weapons.

Research Q1: what problems did Tamaz and Nuri encounter when making their games, and how did they solve them?

According to our analysis, over the course of making their two games, Tamaz and Nuri encountered 23 problems (see Table 1). These problems related mainly to issues with either the player’s character or the enemy character’s attack, health, or movement in both games. For example, in “SMASH,” Tamaz and Nuri managed to get one of their characters, Megaman, to shoot bullets, but the bullets did not cause any damage to the other player. Regarding actor movement, in “Mario and Luigi,” Tamaz and Nuri experienced problems getting goombas, easy-to-defeat enemies, to move around independently, and to get their boss characters to fight independently against the player’s character. These character problems clustered around two central issues related to the game’s main design idea. With “SMASH,” most problems related to attacking the opposing player and inflicting damage; with “Mario and Luigi,” most problems related to enemy movement and attacks.

Table 1. Problems encountered and solved by Tamaz and Nuri.

Problem category	Description	Empirical example	SMASH	Mario and Luigi	Sum
Actor attack	Player or enemy actor not attacking or causing damage	Megaman’s bullets are not causing damage	4	3	7
Actor movement	Player or enemy actor not moving	Bowser is not moving	1	2	3
Actor health	Player or enemy actor not taking damage	Goombas are not dying	–	3	3
Level characteristics	Level feature not working	Added music causes an error	–	3	3
Technical	Issues with hardware or software	Stencyl not working properly	3	4	7
Sum	–	–	8	15	23

In addition to character behavior problems, Tamaz and Nuri also encountered issues with their level designs, such as when the music they wanted to add to “Mario and Luigi” did not play or when they did not know how to create a lava element on their level. Apart from issues related directly to their games, Tamaz and Nuri also encountered technical issues with either their hardware setup or the way in which Stencyl worked. For example, when working on “Mario and Luigi,” Nuri’s screen suddenly went black. After a moment of trying to find solutions, Nuri found that the cables connecting the computer to the screen had become detached, and he re-connected them. On another occasion, when working on the first level of “SMASH” on Tamaz’s computer, Stencyl directed them to download new software to test the level they had created. However, downloading required administrative rights, which neither they nor Mrs. Klein had. After trying several ways to get around the issues on Tamaz’s computer, they adapted and decided to move over to work on Nuri’s computer, which did not have the same issue.

The problems regarding different character and level features stemmed mainly from Tamaz and Nuri working with ready-made stock material downloaded from StencylForge. While these resources made their game-making quicker and easier, the resources also needed to be adjusted or modified to fit Tamaz and Nuri’s game design. Often, the downloaded character had more behaviors than they needed, or they wanted to change something about them (e.g., the amount of damage inflicted). At other times, Tamaz and Nuri wanted to use just the animations but none of the character’s behaviors. However, making these modifications broke the underlying code structure of the downloaded resource and led to problems that needed to be solved.

Tamaz and Nuri solved these problems through a process called “just trial and error.” Our analysis revealed that this process involved four phases: 1) problem finding, 2) discussion about a solution, 3) implementing the solution, and 4) testing the solution. This four-phase process was not explicitly scaffolded by the teacher, though versions of it could be seen everywhere across the FUSE Studio. Once their game-making had been disrupted by the problem, such as surprising character behavior or Stencyl generating an error report, Tamaz and Nuri would search for the cause of the problem by going through the error report or the various game design screens in Stencyl looking for a sign pinpointing the error or by changing actor or level settings. Once a potential cause for the problem was found, either Tamaz or Nuri would suggest a solution to it. Next, the solution would be discussed and revised, or an alternative solution would be presented and discussed. After this, the potential solution would be implemented by either Tamaz or Nuri, depending on who designed the level. This would then be followed by testing the solution by playing the game. If the solution worked, Tamaz and Nuri would continue making their game, and if not, they would return to problem-finding, discussing, implementing, and testing alternative solutions.

The way in which Tamaz and Nuri went through these phases in practice depended on the complexity of each problem encountered. With some problems, like the blacked-out screen, the cause or the solution was more apparent to Tamaz and Nuri, and there was no need for them to search for the problem or discuss different solutions. When the screen turned black, Nuri proceeded directly to test several solutions without discussing them and found the loose cable connection after a few tries. With more complex problems, like ones related to the actor behaviors and the level characteristics, working through the problem required Tamaz and Nuri to test several solutions and persist with the problem even if they were not sure they could solve it at all. In the following vignette, we narrate one such problem-solving process at length to illustrate how Tamaz and Nuri solved complex problems during their game-making. The example comes from Tamaz and Nuri’s fifth FUSE Studio session working on SMASH.

Example 1: getting the attack to work

The problem initially emerged after Tamaz had added an existing kick animation to his actor’s attack behavior, and they were testing the game (Figure 8). During the test, an error report appeared on their screen (Figure 8a). This surprised them and launched them into the problem-finding phase (Figure 8a, turn 14). A closer inspection of the error report did not reveal any insight into the cause of the issue, and Nuri suggested going back to the design page (Figure 8b, turn 16). Tamaz agreed by closing the error report, leaving the game open in the background, and starting to click through various design pages (Figure 8c, turn 19).

Figure 8. Tamaz and Nuri encounter a problem.

The first solution suggestion emerged moments later after a new test game (Figure 9). After getting an error report, Nuri suggested that Tamaz’s edits had also broken his character’s attack behavior (Figure 9a, turns 35 and 40). Nuri then disagreed with Tamaz about whether Tamaz’s character’s animations worked or not and suggested that the problem was caused by their characters using the same kick animation (Figure 9b, turn 43). Tamaz agreed with Nuri (Figure 9b, 44–45) and suggested that they would add a new animation to solve the problem. Nuri agreed, and Tamaz proceeded to implement the solution by creating a new animation for his character, a single frame with a green dot. The rationale behind the single frame animation was to test whether adding the attack animation would work and, after the test, create more elaborate animation.

Figure 9. A problem is encountered again, and a solution is devised.

The test failed, and Tamaz and Nuri returned to the problem-finding phase with the knowledge that Tamaz’s edits had worked (his actor had turned into a green dot when attacking), but this did not clear the underlying problem. Over the course of the next 15 minutes, Tamaz and Nuri repeated the find-discuss-implement-test cycle six times without success. The repeated failures brought on a clear sense of not knowing what the problem was, with Nuri asking, “What is wrong with this?” and Tamaz replying, “I have no idea.”

The solution that eventually solved the problem emerged five minutes before the end of their FUSE Studio session (Figure 10). After another error report, without discussing it with Nuri, Tamaz started implementing a new idea, creating a new character type for their attack (Figure 10a, turns 409–411). Nuri questioned this solution, but Tamaz explained to him that Stencyl was telling them to add an attack type, a weapon, to their attack animation (Figure 10b, turns 434–445). Nuri went along with this begrudgingly and expressed disbelief that the solution would help (Figure 10c, turns 447–451).

Figure 10. A solution regarding actor types is created.

However, creating the new character type, a bullet, solved the problem (Figure 11). Although both Tamaz and Nuri were expecting to see an error report, to their surprise, the game loaded and allowed them to play normally (Figure 11, turns 468–471). They also realized that the bullets should cause more damage (Figure 11, turns 475–476). Once Tamaz and Nuri were back to editing the bullets, Nuri reflected on the overall process of solving the problem by commenting, “Ok that’s all we needed I guess” (Figure 11, turn 485).

Figure 11. Problem solved by adding actor types.

Overall, Tamaz and Nuri’s way of solving problems by “trial and error” was a successful strategy and helped them to be creative in Stencyl and to design stable, playable games. This is evident from how both the number of problems Tamaz and Nuri encountered and the time they spent on solving them significantly dropped after their fifteenth session working on the games (see Table 2). Tamaz reflected on this stabilization when discussing how they had learned through the problems they encountered during their first levels: “Yeah well um at this point since we did a lot of levels before, we know how to do most of the levels ‘cos we experienced problems with the first few. Now it is just getting creative with the levels and making them different.”

Table 2. Number of problems and times spent on problem-solving per game-making session in the FUSE Studio.

Research Q2: how did Tamaz and Nuri use what they had learned from the challenge when making their games, and what new actions did Tamaz and Nuri engage in?

Our analysis of Tamaz and Nuri’s game-making revealed that Tamaz and Nuri used many of the core game-making actions the Game Designer challenge had taught them when making their games. Specifically, Tamaz and Nuri used what they had learned from the challenge to design their levels as well as to modify the design and the behavior of their characters. For example, Tamaz and Nuri used a block element template downloaded from StencylForge to design the levels of both “SMASH” and “Mario and Luigi,” much like with the game they worked on in the Game Designer challenge. In addition, actions like changing the jump force of the character or having the character shoot bullets were actions that Tamaz and Nuri had learned to do through the tutorial videos of the challenge and then employed when editing characters in their own games. The challenge had also taught Tamaz and Nuri that they could test individual scenes instead of the whole game, a feature which made creating the numerous consecutive levels of “Mario and Luigi” manageable.

Over the course of their game-making, Tamaz and Nuri became more adept in these actions. This can be seen by looking at the rate at which they created new levels across the sessions. Twenty-one of the 29 levels (∼72%) were created between sessions 16 and 26 (see Figure 5 at the start of the section). This observation also aligns with Tamaz’s quote above about getting better at problem-solving, meaning they became proportionally more productive even as the complexity of the game levels increased. Once the problems regarding character behaviors and levels had been dealt with, Tamaz and Nuri could become more creative.

In contrast, our analysis also revealed that there were moments in Tamaz and Nuri’s game-making when they struggled to create something that had been explicitly instructed in the challenge tutorial videos. For example, when working on the first level of “SMASH,” Tamaz and Nuri managed to create bullets that their respective characters would fire at their opponent. Creating this specific actor behavior had been covered during the third level of the Game Designer challenge, and the creation of new character behaviors in a more general fashion on the previous level. Tamaz and Nuri managed to create bullets and get their characters to fire them, but they did not manage to make the fired bullets disappear once they had hit the opponent’s character or a block element on the level. This resulted in the game screen being filled with fired bullets, which eventually crashed the game. The way to code fired bullets to “kill themselves” when hitting a character or a level element was part of the challenge tutorial video, but Tamaz and Nuri did not do this or return to the challenge instructions when trying to create their bullets. Overall, this not-using-the-challenge-tutorials and other similar resources for help characterized Tamaz and Nuri’s game-making. The only time they asked for help was during their first game-making session when they asked their facilitator, Mrs. Klein, to help them get Stencyl working properly on Tamaz’s computer.

In turn, when focusing on how Tamaz and Nuri’s game-making extended beyond the support of the challenge tutorials, our analysis has shown that the game-making created both the need and the opportunity for Tamaz and Nuri to expand and further develop their skills and know-how. This was exemplified by the way Tamaz and Nuri learned to use Stencyl in more extended ways and how they incorporated other software and resources as part of their game-making. In terms of Stencyl, one of the things not covered by the challenge tutorials was how to create a new game and new levels in Stencyl. While these actions per se are not complex (much like creating a new document in a word processor), they did require Tamaz and Nuri to engage in and explore things they had not done before with Stencyl, like defining the size (the width and the length) of a level in pixels and naming consecutive levels logically. In contrast, the use of StencylForge for downloading materials for their games and sharing their finished products, as well as learning to read the error reports the software generated, exemplify more elaborate extensions of Tamaz and Nuri’s Stencyl use. Neither the use of StencylForge nor the error reports were referenced at all in the challenge tutorials; these were entirely ‘brought in’ by them.

In addition to learning how to use Stencyl in more extended ways, Tamaz and Nuri also incorporated other software and resources into their game-making. For example, Tamaz and Nuri learned how to use Pencyl, an image editor bundled with Stencyl, to create the bullets for their games, as well as to edit the still images they used for their boss characters in “Mario and Luigi.” In addition, Tamaz and Nuri used StickIt, a Windows application, to store their design ideas for different levels as well as basic game infrastructure information for various features, like the amount of gravity and RGB color codes, for a more consistent gaming experience. A more elaborate example of using other software as part of their game-making was Tamaz’s attempt to create character animations by himself with Piskel, a sprite creation software he had learned about from his friend Emil, who had created his own productive deviation in his FUSE Studio using Piskel. Over the course of several FUSE Studio sessions, Tamaz learned how to use Piskel and managed to create usable actor animations. However, he did not find a way to transfer the animation files from Piskel to Stencyl. In addition, Tamaz and Nuri also used various existing level designs from commercial games as inspirational resources for their own level designs. In practice, Tamaz would have an image of an existing level design on his screen while Nuri designed their level or would look up ideas for levels from other games they knew. However, as a new action, using inspirational material did not last long as Tamaz and Nuri started to self-identify as game makers with their own design ideas over the course of the spring.

To summarize, our analysis shows that Tamaz and Nuri used what they had learned from the challenge to make their games but also extended well beyond that by learning how to use new features of Stencyl and other software as part of the process. Although Tamaz and Nuri could have made more use of the available help resources during their deviation, being allowed to follow their interest beyond the challenge of design significantly enriched their learning about designing games.

Discussion

Learning is often described with metaphors of journeying, traveling, or moving (e.g., Engeström, 2008; Tateo, 2019). According to these metaphors, students in school follow their teacher down the curriculum path to learn. Most studies on student interest focus on students who stay on this path and show that interest can be a powerful motivator for their learning (e.g., Renninger et al., 2015). In contrast, in this study, we wanted to find out what students learn if they step away from the path and are allowed to follow their developing interests beyond the curriculum to deviate productively. To us, productive deviations represent a largely unexplored and potential area of research on student interest in school, given what is known from out-of-school studies on interest (e.g., Barron, 2006; Stevens et al., 2008b).

To understand the learning potential productive deviations possibly entail, we focused on a case of extreme productive deviation during which two sixth-grade students—Tamaz and Nuri—spent more than half of their in-class FUSE time over the year (∼22.5 hours) to create two computer games, something anticipated but not explicitly intended or instructed by the pedagogical design of FUSE. The results of our ethnographic analysis of Tamaz and Nuri’s game-making showed that the deviation formed a significant learning experience for them. During their deviation, Tamaz and Nuri solved complex problems and learned new game-making skills by exploring the opportunities offered by the software they used. Significantly, this learning was spread across the full duration of their deviation. As a result, in his own words, Tamaz “had learned a lot about computer science,” had learned to be creative with computers, and to problem-solve.

Our study offers a central contribution to research on student interest in school: When students’ interests are piqued, and they are allowed to follow them outside the curriculum, this can lead to substantial learning. By this, our study provides further evidence to support Azevedo’s (2006) argument that students’ interest extensions, like productive deviations, are not necessarily antagonistic to curricular goals. Instead, if the right classroom arrangements are in place, as we have argued they are in FUSE Studios, they can fuel them. More specifically, our study shows how rich the learning embedded in these extensions can be. In addition to learning specifically about game design and working with computers, an essential part of this richness was how Tamaz and Nuri were allowed to control and direct the deviation. By being allowed to go beyond the structure of the challenges and their FUSE Studio, Tamaz and Nuri were also allowed to teach themselves more than a little about what learning to create computer games ‘in the wild’ meant (e.g., Hutchins, 1995; Livingston, 2008) in a place (i.e., school) that tends to present students with largely already tamed activities.

In addition, our study also demonstrated what a more encompassing approach to student agency, especially its transformative aspect, would mean for interest studies, conceptually and methodologically. Conceptually, the notion of productive deviation provides a way to theorize how students’ interests develop in school in ways that align with but are not limited to the confines of the curriculum or its implementation. Moreover, the notion allows for a fuller conceptualization of what the core aspects of interest—autonomy and choice (Hidi & Renninger, 2006)—mean in school contexts. Echoing Azevedo (2011), this suggests that productive deviations could be understood as a paradigmatic case of interest-driven learning in schools or of self-directed learning more broadly. It starts with what the curricular activities set in motion, but by supporting surrounding arrangements, it also gives students the opportunity to go in directions of their own making. Given that this interest-driven learning is an emergent phenomenon and not fully predictable (e.g., Valsiner, 1992), our study design offers a methodological blueprint for their study. The FUSE Studio model, with its scaffolds and allowances for interest development, paired with ethnographic tracing of the various interest pathways students create when working in the studio, could also be applied in future studies on interest-driven learning (cf. Ramey & Stevens, 2019). One future methodological direction could be to explore what impact further support could have on the productive deviations and how they develop, in the form of connecting students like Tamaz and Nuri with outside expertise, for example. Another similar avenue that could be explored would be to continue tracing the deviations into other spaces in children’s lives to understand how interest-driven learning continues there. For example, Tamaz and Nuri often referred to working on the games at home and elsewhere outside their regular FUSE Studio time. Such tracing could provide opportunities to understand the formation of interest ecologies (Barron, 2006) around children’s interests as well as the development of their longer-term projects (Hilppö & Rajala, 2023).

Overall, an important question that our study raises relates to the educational value of productive deviations. Arguably, against the backdrop of an ethos of measured educational performance and effectiveness (e.g., Ambrosio, 2013), Tamaz and Nuri’s method of trial-and-error could be seen as being ineffective, even wasteful. Yet, sometimes the journey itself is more important than where or how far you go. If we take our cue from Plutarch (1927), the value of Tamaz and Nuri’s deviation lies in the fact they surpassed the given and followed their interest. Moreover, if one of the central goals of education is subjectification (Biesta, 2020), becoming an irreplaceable person through education, then productive deviations could be seen as a manifestation of this process. Instead of learning the same as everybody else or being allowed to make fixed choices within the confines of the curriculum, productive deviations or similar interest extensions provide an opportunity for learners to particularize their pathway through formal education. In the case of Tamaz and Nuri, in the contexts of their FUSE Studio, their class, and the Stencyl community, this meant they became people who were recognized through their games and their skills as game-making experts (cf. relative expertise, Stevens et al., 2016).

In part, our study speaks to an emergentist perspective on the curriculum (Osberg & Biesta, 2008; Stevens, 2000). A curriculum that builds on students’ interests and supports their interest development means allowing time, support, and other resources for students’ explorations as they manifest themselves, instead of a curriculum of predetermined goals and lesson structures. However, what should be highlighted is that Tamaz and Nuri’s deviation emerged from their prior engagement with the FUSE Studio challenges and on how their FUSE Studio was organized (for details, see Hilppö & Stevens, 2023). While it is possible that their interest in video game design might also have emerged without them, our analysis shows that the FUSE Studio’s social and material infrastructure (Stevens et al., 2016) was central to their process. That is, fostering student interests also means providing structures that generate and spark interest without curtailing them. In this sense, the educational value of productive deviations is then two-fold: in addition to being important in themselves, they also speak for the quality of the setting in which they emerge. Switching metaphors, productive deviations in this sense could be seen as a keystone species of learning infrastructures, especially ones that espouse supporting student interests or educational quality more broadly. For teachers, who are often on the watch for the invasive species of students being off task, productive deviations provide a clear alternative target, one which instead tells them of the vitality of their classroom and that their students are taking what they learned to productive new directions. Overall, Tamaz and Nuri’s case shows a paradigmatic case of securing what Dewey referred to as securing “the one thing needful in education” (1913, p. 97), that of student interests as a starting point and an endpoint of designed learning environments.

Acknowledgments

We want to thank the teachers, students, and their parents involved in this study for their time and help in making this study possible. We also want to thank Kay Ramey, Jake McMullen, and Lasse Lipponen for their help with the study.

Disclosure statement

We have no conflict of interest to disclose.

Additional information

Funding

This work is supported by the National Science Foundation under NSF grants DLR 1348800, DLR 1344724, and DLR 1657438.

Notes

1 Elsewhere, Stevens has also referred to this with the metaphor of “off road,” to distinguish it from the common complaint in education that students are “off task.”

2 A side scroller here refers to a game genre in which the scene the players play moves from left to right, like in the first Super Mario Bros game by Nintendo.