Introduction

The field of STEM education is presently in a phase of transformation both internationally (STEM Task Force Report 2014) and in Australia more specifically (Panizzon and Corrigan 2017). The political imperative of this transformation centers on economic development emphasizing a need for innovation and entrepreneurial thinking in STEM research and education (Office of the Chief Scientist 2015). At a policy level, Panizzon and Corrigan (2017) suggest there is a lack of clarity about how entrepreneurial education and STEM education should be connected. However, at the level of teaching practice in schools and higher education within Australia, connections are being developed between STEM education and entrepreneurial education.

Entrepreneurial education involves teaching and learning across two interrelated sub-disciplines of entrepreneurship and enterprise (QAA 2018). Entrepreneurship concerns the application of enterprise or entrepreneurial thinking for “the creation of cultural, social or economic value,” which typically involves the formation of a business or social venture (QAA 2018, p. 7). As a precondition for entrepreneurship, entrepreneurial thinking involves a capability in the “generation and application of ideas,” that may be applied in a broad variety of settings (QAA 2018, p. 7). For example, Aziz and Rowland (2018) recently described biotechnology graduates in Malaysia as understanding the need for entrepreneurial thinking in STEM professions to enable the systematic recognition and evaluation of new ideas. The connection between entrepreneurial thinking and the work of biotechnology graduates highlights a need in higher education contexts for more explicit teaching about the role of entrepreneurial thinking in the STEM professions.

My orientation in this study is toward the confluence of entrepreneurial thinking and STEM education by taking into consideration a contemporaneous shift in thinking about STEM as a transdisciplinary enterprise (cf. English 2016). Integrated STEM is regarded as a transdisciplinary way of teaching STEM that increases its complexity and promotes the refocusing of STEM education around authentic problems (cf. Davis and Sumara 2006; Nadelson and Seifert 2017). Such reimagining of STEM as an integrated transdisciplinary enterprise requires rethinking in how preservice teachers engage with STEM and its authentic contextualization (cf. Shernoff et al. 2017).

An example of an authentic STEM context is highlighted in the paper by Aziz and Rowland (2018), as they illustrate connectivity between the transdisciplinary field of biotechnology and entrepreneurial thinking. A particular focus for Aziz and Rowland (2018) was to explore the variety of thinking skills that entrepreneurial biotechnology graduates may need in their professional lives. Following that example, the inclusion of entrepreneurial thinking in STEM education, for preservice teachers, offers an innovative educational approach for learning about problem orientation, contextualization, and authenticity. In terms of the contextualization of integrated STEM, authentic problems may be complex societal issues that we identify as wicked and ill-defined (Rittel and Webber 1973). These are often big problems within which smaller localized problems are nested, which may enable the problem to be scaled down to manageable localized contexts in educational settings.

A further aspect of complexity involves an understanding of the origins or ontology of ideas, opportunities, or problems in entrepreneurial and STEM contexts, and this ontological issue may be regarded as an area of common ground for these disciplines. In entrepreneurship contexts, understanding how ideas, opportunities, or problems are not discovered but are generated is very important when teaching entrepreneurial thinking because it provides a sense of agency for entrepreneurial actors (Jones 2011). Similarly, in STEM education, ideas or problems may be generated from the everyday lives and passions of students, which are often related to wider societal issues (Davis et al. in press). Like the experiences of undergraduate business students, preservice STEM teachers, particularly in undergraduate programs, must also learn to develop or define authentic problems (cf. Jordan et al. 2014). To address this need, I look toward the end user-focused problem validation processes emerging from the dot.com crash in 2000 (Blank 2013, 2018; Osterwald and Pigneur 2010; Ries 2014), because these forms of validated learning have become core features of authentic entrepreneurial thinking over the past two decades. More specifically, in the present study, my focus is on the application of entrepreneurial thinking in an integrated STEM education context where I adopt a problem validation technique used by entrepreneurs as part of their thinking in the development of lean startups (Lean Startup Machine 2018). I also apply a reflective approach to teaching, aimed at enhancing the learning experiences of my preservice STEM teachers.

Aim and research question

The aim of this study is to explore preservice teacher experiences of validated learning during an integrated STEM investigation. My research question is: How do preservice teachers perform and experience entrepreneurial validated learning as part of a STEM investigation?

Conceptual framework

The concept of validated learning draws from entrepreneurship in the lean startup model described by Ries (2014). Validated learning is a rigorous process designed to test the action taken in developing an idea in situations of extreme uncertainty. The progression of an idea is validated incrementally against feedback from owners of a problem who we may call potential early adopters or end users of the project’s outcomes. Because early ideas and early solutions are validated without being perfect, there is an expectation for small, managed, and nondestructive failures to be experienced as the basis for genuine learning (cf. Simpson and Maltese 2016). In this way, validated learning and the notion of failure are not used to rationalize unmanaged risk taking and big failures after the event. Instead, validated learning is about continuously checking that ideas and actions are valued by end users on an incremental basis as learners’ experiences of a project unfold.

To operationalize validated learning in a practical way, this study draws on the ideas presented in a validation board offered as a free tool for entrepreneurs by Lean Startup Machine (2018). This tool is commonly used in the early stages of developing entrepreneurial ideas using validated learning. In the present study, I used a simplified validation process, which I designed for nonbusiness entrepreneurial contexts such as STEM classrooms.

My simplified validation board comprises of three core questions: (1) What is the problem; (2) who owns the problem; and (3) why is it a problem. The response to question one needs to be succinctly stated, preferably in ten words or less. Succinct and precise wording of the problem enables constructs to be identified and evaluated. In this sense, it is similar to the statement of a research question or hypothesis in scientific research (cf. Valiela 2001). Addressing question two also requires a high level of precision, evident in entrepreneurial contexts where much time is spent defining who owns the problem by building a very specific persona of potential end users (cf. Aulet 2013). Greater precision in defining an end user persona will contribute to data quality in the validation process by ensuring surveys are directed at the right people. The third question of why the problem is believed to be a problem is a way of listing assumptions about the answer to question one. This is an important list as it may have implications for the answers to both questions one and two. Question three may be best addressed via a team brainstorming activity, and, once listed, the assumptions (i.e., the answers) should be prioritized from most important to least important.

Once assumptions are prioritized, the process of validation commences. Assumptions are tested by defining a method for engaging with the people identified as problem owners, and collecting data at the lowest cost, and as quickly as possible. Predetermining a set of minimum success criteria is also important for defining the point where an assumption is deemed valid or invalid.

If the validation process is being applied as suggested above, it is very rare that a problem is successfully validated via this process on the first-run-through. Typically, in educational contexts, the first or second assumption is found to be invalid, meaning the assumption is false and the problem is invalidated. This requires a new problem to be defined, which is called a pivot in entrepreneurial language (Ries 2014). The pivot is usually derived by taking one of the most important assumptions and reshaping it into a new problem statement, based on what has been learned through the validation process. Once this new problem is defined, the validation process is applied again, and this is repeated until the most important assumptions about the problem are validated. In the context of the present study, successful validation of a problem means it is valued by a particular population, or type of person, and there is value in proceeding with the STEM investigation.

Methodology: a phenomenological orientation

The present study is informed by a phenomenological orientation (Van Manen 1997) to explore preservice teacher performances and experiences of validated learning during the problem definition phase of a STEM investigation project. Phenomenology involves rich description and interpretation of human experiences as a way of understanding other people’s perspectives. In the present study, I have adopted a phenomenological orientation to understand how study participants have performed validated learning as a team, in relation to the earlier conceptual framework. I have also explored participant experiences of their performed versions of validated learning by analyzing their individual reflective journals.

This methodological orientation draws on preservice teacher’s reflections to thematically describe the performance of validated learning and their experiences of those performed activities. Performance is described by analyzing data from project reports of two different teams. From these two teams, description of individual experiences is informed by reflective journals maintained over the duration of course-work projects as part of the assessment. Such experiences reflect not just what preservice teachers were doing in an objective sense, but also their subjective experiences such as feelings of frustration, and how these experiences changed over time (cf. Bellocchi 2018; Bellocchi and Ritchie 2015; King et al. 2017).

To achieve the description of preservice teacher experiences, I adopt a position of indifference to the data (Van Manen 1997). This means I describe preservice teachers’ experiences as they are, while seeking to withhold a priori theoretical or normative judgments. For example, if they apply a technique that contradicts what I taught them, I am less interested in critiquing their technique, but more interested in understanding what actions they performed and how they experienced the consequences of their actions as a learning experience. This is an important methodological approach for understanding how preservice teachers learn through doing entrepreneurial thinking.

Methods

Study context

This study was conducted in a capstone course that seeks to unify learning from a sequence of earlier courses through an investigative project. The capstone course in this study is part of an undergraduate program for science and mathematics preservice teachers. Ethics approval was obtained from a university human research ethics committee, and all study participants provided written informed consent. The rationale for this course is to develop preservice teachers’ skills in defining authentic problems and to investigate problems using rigorous, qualitative and quantitative methods from the field of integrated STEM. The course is delivered over a 13-week semester with a blend of explicit teaching and mentor-supported team-based project work. Direct instruction was delivered at the beginning of workshops on topics such as problem definition and validation from entrepreneurial perspectives, science inquiry design, measurement theory, question and variable formulation, statistical methods, design thinking and design cycles, project planning skills, report writing, reflective writing, ethics, teamwork, and emotions management. Student assessment comprised of two team tasks, a project plan and a project report, as well as an individual reflective journal as a focus for personal learning.

The course was co-taught by me, as a science educator and course coordinator, and a professor in mathematics education. The total number of preservice teachers was 47, who self-selected into 12 project teams for the duration of the course. From this class, 34 preservice teachers consented to participate. Preservice teachers were mostly in the first semester of their third year in a 4-year Bachelor of Education degree with secondary science and/or mathematics majors, in an Australian university.

Data production and selection

Data sources in this study comprise of the assessment items submitted by preservice teachers including a team project plan, a project report, and individual reflective journals that document personal learning experiences throughout the course. The data analyzed in this paper were selected from two project teams, comprising of seven preservice teachers in total. These two teams were selected from six teams that had fully consented to participate in the study. Of the six teams for which all members had provided consent, two of the teams adopted ideas that were provided by me as the teacher. By selecting a given topic, the originality of ideas was diminished for the purposes of this study and for this reason, these teams were excluded. Of the other two teams that were excluded, both adopted a weak form of problem validation by following a more traditional approach of literature-driven problem identification. In this study, my focus was to understand how preservice teachers experienced validated learning where ideas were derived from real-world contexts, rather than intellectual perspectives interpreted from the literature. This is an important distinction because the traditional method leaves open the question as to what literature is actually worth looking at in the first place. For this reason, the final two teams selected for this study were chosen because of their process that may be summarized as moving from the initial idea, through a strong entrepreneurial validation process, to the relevant literature and then to the STEM investigation phase. A summary of the project titles and individual pseudonyms is shown in Table 1.

Table 1 Summary of projects and preservice teachers
Full size table

Methods of data analysis

To describe preservice teacher experiences of validated learning, data from individual reflective journals are analyzed using a phenomenological technique (Van Manen 1997) similar to inductive content analysis (Elo and Kyngas 2007). Compared with content analysis, the phenomenological approach places a greater focus on thematic description, and a lesser focus on defining abstract constructs. For this reason, conventional content analysis technologies, such as NVivo, were not applied. My phenomenological method involves wholistic reading of the data to understand the fundamental significance of the data, and selection of particular statements or phrases, which are essential for understanding participant experiences. The task in developing phenomenological themes is, “to hold on to these themes by lifting appropriate phrases or capturing in singular statements the main thrust of the meaning” of participant experiences (Van Manen 1997, p. 93). Through my phenomenological orientation, I seek to describe participant experiences without losing their meaning. From the reflective journals, I identify similarity between words and phrases to enable collation of data into five themes, which I defined as: challenges, interest and emotion, diversity, mentor interaction, and idea generation. These themes formed the basis for headings in my “Results and Discussion” section, to describe preservice teacher learning experiences of the problem validation process, where these descriptions include numerous samples of raw data.

Quality criteria for evaluating data

My quality criteria for evaluating data are drawn from the fourth-generation evaluation framework of trustworthiness and authenticity (Guba and Lincoln 1989). These criteria were previously applied in a recent phenomenological study in an educational context (see Davis and Bellocchi 2018). I have described abstract ideas as being evident in the localized concrete reflections of study participants to indicate a dialectic relationship (Roth 2009) between their subjective, concrete experiences and their objectified abstract ideas as representative descriptions of those experiences. This is my basis for making general descriptive statements as a form of theoretical transferability (theoretical generalizability) in this paper (Eisenhart 2009). Theoretical transferability enables the formation of abstraction from concrete experiences, and this is facilitated by my adherence to the criteria of dependability. Dependability is evident in my study as I have presented extracts from participant reflective journals and connected these with my interpretation of data to establish traceability. To enhance traceability of data (Guba and Lincoln 1989), I reference direct quotations by citing the preservice teacher’s pseudonym, the week, and the line number in their journal extract as presented in Appendix A of ESM. For example, a quote from Mike’s journal in week 2, from line 5, would have the in-text citation of, Mike W2L5.

Results and discussion

Performance of validated learning: train services

Preservice teachers in team 1 (Mike, Anna, Dan, and Kim) developed their investigation around the need to explore overcrowded train services in the city of Brisbane. This idea was derived from team member’s personal experiences of overcrowded trains and their personal frustration with this system. The initial idea generated much discussion across the class peer group, and this initial, informal validation prompted the team to investigate the issue further. Their investigation of publicly available data, including media reports available online, was indicating significant overcrowding during peak hour services with the main northern train line being notorious with commuters.

In their project plan, the preservice teachers identified the problem as: A need for better scheduling of trains to reduce over-crowding and improve resource usage. The owners of the problem were defined as peak hour commuters. To validate this problem, a survey was developed where preservice teachers stated, “The aim of the questions asked in this survey was to discover how the capacity issues on trains affect the commuters and the overall satisfaction of the service.” Their survey was conducted online using social media to target northern Brisbane train commuters, and they collected data from 50 people. The preservice teachers survey questions comprised of:

  1. 1.

    “How many times a week would you say that you catch the train?

  2. 2.

    Do you often experience delays to your train service due to capacity issues? (i.e., the train being at full capacity)

  3. 3.

    Have you ever been on a peak hour train where there is no room to move?

  4. 4.

    Would you say that the fees you pay to catch the train are reasonable?

  5. 5.

    On a scale from 1 to 10, how satisfied would you say you are with the train service?”

The survey questions generated by the preservice teachers (i.e., questions 1–5 above) were adopted by this team as their approach to the problem validation process I described in the earlier conceptual framework. Their survey questions were not scientific questions because the problem focus for the STEM investigation had not yet been defined. It is also important to note that by using a survey in this format, the preservice teachers were making their own deviation from the problem validation process they had been taught. The survey should have been testing their specific assumptions about the problem they had identified; however, the team did not clearly identify their assumptions. With a more complex problem, this team may have found it difficult to pivot or redefine the problem if the need eventuated.

As part of their methods for validating their problem, team 1 reported their minimum success criteria for questions 2–5 of the survey as being at the 50% level, meaning that at least half of the respondents needed to answer yes for problem validity to be established. The structure of these criteria in relation to the questions is problematic because of the style of questions posed by preservice teachers. In addition, the success criteria were not statistically determined; instead, it was based on a value judgment made by the team. In an actual entrepreneurial context, the establishment of minimum success criteria may be more rigorously determined and better aligned with the question structure. In the educational context of this study, the purpose of this part of the process was aimed at having preservice teachers engage with potential end users of their innovation. While the rigor of their process could have been better, the experience of end user engagement in generating the idea or problem remained a valuable learning experience, as discussed later.

Performance of validated learning: waste recycling

The preservice teachers in team 2 (Sally, Jean, and Emma) developed their idea out of a strong personal interest in recycling and environmental awareness, by deciding to focus on waste disposal from food outlets on the university campus. They commenced their problem definition with online social media research into data about solid waste management in Australia. Their preliminary exploration highlighted China’s recent ban on imports of dirty waste that has meant Australia currently, in 2018, has very limited options for waste recycling. This situation has raised public awareness of the issue of waste management in Australia, and for this reason, the issue was considered important by these preservice teachers. To make their investigation achievable, the team focused on the university campus as a site for analysis and explored the university’s policies on a green workspace and low carbon footprint.

Despite these policies, the team observed a problem on campus, which they defined as: Waste on campus is frequently disposed of incorrectly by the campus population because people are not interested in this issue. The team focused on students as the primary owners of the problem given their majority within the university population, but other stakeholders such as food outlet managers were also identified. There was close adherence by the team to the problem validation process as they identified three assumptions about their problem and prioritized these from most to least important as follows:

  1. 1.

    “General disinterest in recycling and exhibiting environmentally-friendly attitudes.

  2. 2.

    Lack of basic knowledge on materials that are considered recyclable versus general waste.

  3. 3.

    Lack of recycling bins on campus.”

To test these assumptions, the team conducted an online survey of campus students using social media (61 respondents). As their project report stated, “The questionnaire aimed to elicit responses about: students’ knowledge of recyclable materials; common single-use food packaging; preferred methods of accessing information about waste disposal; and attitudes towards obtaining unknown information about recycling and waste disposal.” By stating the above assumptions first, this survey format was much more focused on testing assumptions when compared to the survey of team 1, which lacked a clear focus.

As described earlier in the conceptual framework, the assumptions as listed from one to three above were developed by asking why the identified problem is assumed to be a problem. By asking why, the preservice teachers were attempting to question themselves and to identify and clearly state the assumptions they made when defining the initial problem. This was the process they were taught, and they were able to test their top three assumptions with a single survey focusing specifically on their assumptions. The process was time-efficient for team 2, particularly when they found their first assumption was invalid. By addressing all three assumptions with their first end-user survey, the team was able to quickly pivot the problem. That is, they could quickly redefine the problem when it was invalidated by end-user feedback. The performance of the process by team 2, as outlined in the conceptual framework, illustrates the efficiency of following the entrepreneurial validation process.

The efficiency of the validation process became evident when the team found their first assumption to be incorrect, because most end users they interviewed held very positive attitudes toward correct waste disposal. In their reflections, team members’ stated their surprise upon finding people to be very interested in the issue, but lacking sufficient knowledge to dispose of waste correctly. This enabled a pivot to the problem they were generating. The team restated their new problem as, “The frequent incorrect disposal of waste on campus correlates with a lack of basic knowledge on what and how to recycle.”

Experiences of validation processes

Data from five of the seven preservice teacher reflective journals are presented in Appendix A of ESM. Two of the preservice teachers may be classified as “non-reflectors” (Chirema 2006, p. 194). The classification of non-reflector is made on the basis that their journals mostly contained objective descriptions of what they did, rather than subjective reflections on their learning experiences, and for this reason, their journal extracts were not published below. In the following sections, I outline preservice teacher experiences of developing their passion-led ideas for their STEM investigation projects under the thematic headings: challenges of idea generation; diversity, interest and emotion; and challenges of an idea pivot.

Challenges of idea generation

I commenced teaching the course by discussing the notion of integrated STEM and authentic, wicked problems, before introducing the problem validation process. Generation of ideas by preservice teachers was enhanced by the open-ended structure of the assessment where they were encouraged to generate and validate their own problems for investigation. This was not a simple, linear, or emotion-free process. Idea generation was very challenging as indicated by the preservice teacher with the pseudonym Jean who reflected in week 2 as she “realised just how much planning goes into a STEM investigation” (Jean W2L1) and that she “didn’t realise until now how hard it is to actually think of a problem from thin air” (Jean W2L7). Mike reflected on his misconceptions about how to start the project. He describes how this “evoked feelings of discomfort and made me feel disinterested as I hadn’t previously been allocated this much flexibility” (Mike W2L3). He was referring here to the open-ended design of this project, which added a level complexity for learners because I did not impose boundaries. Anna also noted how the task was “broad” and defining a problem was “challenging” (Anna W1L8). In team 2, Emma stated how the project was “really exciting” but she also hoped they would “find a clear way forward” indicating her sense of uncertainty (Emma W2L15). This is further reflected by Sally who describes herself at this early stage as being “excited by this process though apprehensive” (Sally W2L8).

These experiences by preservice teachers are important for teachers to appreciate because they indicate preconceptions that idea generation and validation would be simple, which it is not. To guide preservice teachers, I described the problem validation process from the perspective of entrepreneurial contexts and directed preservice teachers to Aulet (2013) who suggests innovative projects are generated by people who have an idea, a technology or a passion. Ideas generally relate to current knowledge of existing processes in need of improvement. Technology refers to something which is newly developed, but not yet deployed. A passion is driven by personal confidence of developing something from current skills and deep interests. As the teacher I encouraged preservice teachers to think about these three key sources for generating ideas, and the two teams in the present study generated ideas from the team members’ mutual passions and interests.

Preservice teachers seem to find stating an initial idea is quite simple; however, the process of entrepreneurial validated learning becomes challenging when learners are forced to get-out-of-the-building (Ries 2014) and test their assumptions. Validated learning is not part of conventional STEM education; however, its’ introduction in this course enabled preservice teachers to gain a deep experiential understanding of the connections between people’s everyday lives, issues that people value, and the possibility for STEM to provide valued solutions. Such understanding is important for future teachers of STEM who will need to contextualize curriculum in secondary school STEM education.

Diversity, interest, and emotion

To focus preservice teachers’ thinking during idea generation, I guided teams toward taking their big ideas and localize or scale their problems down to a manageable task. Team 1 found a common interest in their dissatisfaction with public transport with a focus on the city’s train system. This problem required further definition as they initially considered a variety of sub-issues such as reliability, capacity, pricing, trip quality, and duration of trips (Mike W3L5). Finally, they decided to focus on train capacity and overcrowding particularly in peak hours. After identifying a problem to validate, Mike noted in his journal how he was now feeling “really keen” (Mike W2L12) because of the shared clarity around their idea. Finding a shared interest was important for the team and in the case of Mike this was reflected in a positive feeling toward the idea.

Mike also reflected on the teams’ diversity. For example, he wrote, “Although we didn’t have as much transdisciplinary diversity as some of the other teams, we did however bring forth differing personalities, experiences and views which I deemed integral to our success” (Mike, W2L16-18). This was an interesting reflection because within my teaching I had emphasized different disciplinary and end-user perspectives in these entrepreneurial-driven STEM investigations. Moving beyond my explicit teaching, Mike also recognized the more fine-grained personality differences in his team. This diversity was particularly evident in his team with a mix of males and females, as well as team members from three different ethnic backgrounds.

In contrast, team 2 seemed less socially diverse, where all were Caucasian and female, with mathematics backgrounds. Their common disciplinary backgrounds seemed to influence their initial thinking, evident in Jean’s reflection about problems they might address using mathematical skills. This is consistent with Aulet’s (2013) suggestion of drawing from ones’ passions, because these preservice teachers were passionate about mathematics. However, the team’s reflections indicated a shift away from mathematics as they considered their shared passions about broader social issues. Looking at the big issues in society as a starting point was something I had encouraged since the first workshop, with the notion of wicked problems, and this team had certainly taken this approach seriously. As Sally noted in her reflection they, “Wanted to choose a problem that affects each of us on a personal level” (Sally W2L3) and Emma noted how they were looking for “something we all wanted” (Emma W2L5). Importantly, Emma also wanted to “design something that mattered” (Emma W2L6). This team found their mutual passion in their social concern for recycling and waste management that they initially identified at a global and national level, before localizing the problem to the university campus.

These experiences evidence the influence of team diversity, finding shared personal interests, and a level of emotional attachment with learner generated ideas evident in words such “really keen” and “a problem that affects each of us.” The application of entrepreneurial thinking in these two team situations has clearly shifted their focus away from their educational disciplines, toward broader issues extending beyond the boundaries of the university. These experiences not only reflect an appreciation of end user values, but also team members own values as learners. It may be argued that it was their values as learners that led the problem generation process, and ultimately the STEM investigation that followed.

Challenges of an idea pivot

At the point where these two teams needed to validate their particular problems, there was some deviation in the way each team approached problem validation that may have influenced their learning experiences. For team 1, instead of clearly stating their assumptions as to why they believed their problem was a problem, they moved directly to developing a survey. Data from team 1’s project report shows how their survey was used to validate their problem with two questions: “Have you been on a peak hour train where there is no room to move”; and “on a scale from 1 to 10, how satisfied would you say you are with the train service.” The other three questions that they asked did not relate directly to the problem they had chosen to focus on which was a need for better scheduling of trains to reduce overcrowding and improve resource usage. Because they did not explicitly list, prioritize, and test their assumptions the likelihood that possible train commuters would challenge the team’s problem was limited. This limitation was reflected in the lack of reflective notes indicating any such challenges, and I interpret this as a limited learning experience because the team may have benefited from having their values challenged by the different values of end users. As the teacher I would need to address this limitation in the future by ensuring more rigorous application of the validated learning process.

In contrast, team 2 explicitly listed and prioritized their assumptions as to why they believed the problem may be a problem for the on-campus population, and their first survey with 61 respondents directly tested their assumptions. Data from team 2’s project report shows how they first assumed there was “general disinterest in recycling and in exhibiting environmentally-friendly attitudes.” This was invalidated by their survey results with both quantitative and qualitative data showing strong interest in correct recycling practices. Emma reflected on how her team were frustrated by the invalidation of their first assumption and Sally confirms this source of frustration, noting how “the results of the survey were not what was initially expected” (Sally W3L1).

Emma and Sally’s frustration suggest they held an expectation about their initial problem statement as being valid, and this expectation was not met, resulting in a need to pivot in response to their validation process. Their frustration suggests a preconception about the process of problem generation as being simple and linear. Dealing with learner experiences of frustration is an important consideration for the teacher as indicated in the field of science education research (King et al. 2017). Frustration is an experience arising from situations where expectations are not met. It is common in science and STEM investigations and was evident in the present study with reflections containing words such as discomfort, disinterested and frustrating to describe particular situations. King et al. (2017) found school students’ experiences of frustration during science inquiry projects changed over time, and in the present study some preservice teachers reflected upon their own experiences of frustration transforming into positive experiences, such as a sense of achievement.

Despite experiences of frustration being noted, team 2 were able to pivot easily because they had collected data about their other two assumptions, enabling them to rapidly pivot or “define a new problem” (Sally W3L8), without the need for another survey. In the problem validation process pivoting is a practice of taking one of the assumptions (i.e., an answer to the why question) and reshaping it into a newly defined problem. In this case the team reported a pivot to a new problem as “a lack of basic knowledge on what and how to recycle,” which was already validated from the survey data they had collected. The successful outcome from applying this process suggests a degree of perseverance through which earlier experiences of frustration were overcome. The shift in emotional experiences such as frustration (King et al. 2017) and achievement (Bellocchi and Ritchie 2015) are aspects of learning through entrepreneurial thinking that need further investigation in naturalistic learning contexts, such as those described in the present study.

Conclusion

The present study has addressed the question of, how do preservice teachers perform and experience entrepreneurial validated-learning as part of a STEM investigation? The process of entrepreneurial thinking via validated learning is commonly used by startup entrepreneurs, but rarely, if at all, applied as a start point for learning in a STEM investigation process. Preservice teachers’ performances of validated learning as a process were variable, which may have been due to its novelty as a STEM-related process. There is clearly a need for more explicit explanation to preservice teachers about the value of this process as a way to connect a STEM investigation to real-world, authentic issues and contexts.

The introduction of validated learning to the STEM course in this study provided an important learning experience for preservice teachers around the notion of value adding for end users. This experience was frustrating for some, but as a learning experience, it helped preservice teachers make connections between STEM, authentic real-world issues, and people in everyday society. These connections were made possible by the open-ended design of the projects that forced preservice teachers to get-out-of-the-building, to engage with potential end users, and to understand the extent to which others may value the ideas and problems they were generating. This required learners to immerse themselves in end user perspectives and to understand authentic, real-world problems by learning through entrepreneurial thinking. As I have shown in this study, this is a learning experience that is equally important for preservice STEM teachers as it is for entrepreneurship students in an undergraduate business course (cf. Jones 2011).

Finally, as a phenomenological investigation this study is descriptive and interpretative for the purposes of illustrating the possibilities for integrating entrepreneurial education and STEM education. This is an important area of research because it represents the teaching interface between two educational fields that have implications for various international and national innovation policies (Panizzon and Corrigan 2017). While this paper focuses on entrepreneurial validated-learning, there are many other aspects of entrepreneurial thinking that may be applicable to integrated STEM education, and these should be considered when planning future research.

Limitations

There are several limitations to this study. The first is my reliance on reflective journals wherein the preservice teachers were not highly experienced in deep engagement with their learning experiences. I provided lecture materials and readings on how to engage in reflective writing and discussed reflective writing with teams during the course. Preservice teachers were also supported by a thorough marking rubric that described the requirements for their reflective journals. Despite these actions in my teaching, the study was over-reliant on the development of preservice teachers’ reflective writing skills over the duration of the study. The limitation of reflective journals could have been minimized by reviewing the journals progressively and interviewing study participants. A further limitation to this study was the resistance from preservice teachers in engaging with the entrepreneurial validation process. This may have been due in part to their established or conventional views on what STEM is or should be, and how they identify themselves with STEM and entrepreneurial thinking. This limitation raises the issue of preservice teacher identity when faced with the notion of integrated STEM and points to the need for further research into identity formation.

Implications for future research

Further research is needed into problem validation and the application of other aspects of entrepreneurial thinking in the context of integrated STEM education if we are to establish meaningful connections between entrepreneurial education and STEM education. Personal management and self-awareness of emotional experiences in learning are also important, especially where complexity and innovative processes are presented as part of learning experiences. Future research could further elucidate a pedagogy of emotion (Bellocchi 2018) in these fields, which may help integration of entrepreneurial education with STEM education while encouraging greater engagement by preservice teachers. How the entrepreneurial innovations explored in this paper may translate to STEM Education in primary and secondary school contexts is also an important direction for future research.