Toward behavioral learning outcomes: a case study of an experiential learning approach and students’ self-reported facilitators and barriers for pro-environmental behavior

ALC

= Active learning classroom;

EL

= Experiential learning;

ESD

= Education for sustainable development; and

SD

= Sustainable development.

Education for sustainable development (ESD) is no longer only about raising awareness and knowledge about climate change but about learning to transform the world and to realize societal transformations toward pro-environmental behavior (Arbuthnott, 2009; UNESCO, 2018). Even though universities across the globe are looking for ways to reorient their teaching and learning toward SD, they often struggle in finding ways to make their education more systems-oriented, more values-sensitive, more inclusive, more transformative and more transgressive (Mulà et al., 2017; Lotz-Sisitka et al., 2016). The basic academic competencies such as critical thinking, communication and research methods must be nourished with specific key competencies for sustainability such as systems thinking, anticipatory, normative and strategic competence (Wiek et al., 2011). In 2017, the United Nations Educational, Scientific and Cultural Organization (UNESCO) suggested a broader set of key competencies (a number of eight) as learning objectives and goals for ESD, namely, systems thinking competency, anticipatory competency, normative competency, strategic competency, collaboration competency, critical thinking competency, self-awareness competency, integrated problem-solving competency (UNESCO, 2017). These competencies should be applicable in any sphere of education and comprise all the earlier above-named competencies but adding self-awareness competency and integrated problem-solving competency. Learning outcomes of ESD can thereby be cognitive, socio-emotional and behavioral (UNESCO, 2017; UNESCO, 2018). While ESD might successful alter students’ knowledge and critical thinking (cognitive learning outcome) and attitudes (social-emotional learning outcome), research has shown that they struggle to impact on behavioral learning outcomes and do not automatically lead to behavior change (do Amaral and Hess, 2018; Abner et al., 2019; Paige, 2017; Algurén, 2021).

It is often through concrete experience from which learning can be initiated, reviewed, challenged and reconsidered (Fry et al., 1999; Kolb and Boyatzis, 2000). This kind of pedagogy is often mentioned as a critical feature of sustainability-oriented learning, as it enables reflecting on deeper values and assumptions (second order learning), learning how to learn and meta-cognitive learning (third order learning), as well as critical self-reflection (Clark and Dickson, 2003; Wiek et al., 2011; Wiek et al., 2014; UNESCO, 2018). In that way, it can empower individuals to engage in reflective and responsible actions. Kolb, along with a few other scholars and practitioners, emphasized the power of “learning by doing” in bringing the three learning domains of behavior, cognition and perception together. As such, experiential learning (EL) and associated learning by doing, represents a promising approach for realizing deep-level learning and the kind of behavior change needed to contribute to SD While there is a lot of research showing that this kind of education can positively influence understanding, knowledge and attitudes, the link to actual pro-environmental behavior is not easily established (Abner et al., 2019; do Amaral and Hess, 2018; Mintz et al., 2014; Paige, 2017).

Indeed, behavior change is complex, several models have been developed to better understand people’s actions and factors driving behavior. One of the first models – the health belief model (HBM) – was established by American social psychologists who tried to understand why people succeed or not with disease prevention strategies in the early 1950s (Rosenstock, 1974). Originally, the model comprised four constructs, namely, perceived susceptibility (persons perception of risk for suffering from an illness/disease), perceived severity (and following consequences of illness/disease), perceived benefits (effectiveness of possible actions to reduce the threat) and perceived barriers (possible obstacles to perform a recommended health action versus profit). The distinction of a person’s perception of these four tenets together will predict the likelihood of a person’s adoption of the behavior. Later, two constructs were added since research with the HBM advanced. One is cue to action, the stimulus that can trigger the adoption of an action, e.g. serious pain (internal cue) or illness of a family member (external cue). The other later added construct is self-efficacy – person’s confidence in their ability to successfully accomplish a behavior, that is used in many behavioral theories and mainly shaped by psychologist Albert Bandura (Bandura, 1997). The model has various limitations and, especially in contexts outside disease prevention, its utility is limited. For example, non-health related behaviors that have their foundation in social acceptability are not described. Further, attitudes, beliefs and norms – individual and social – as well as habits, environmental and economic factors are neither accounted for. Another model, not only intended to explain health-related behaviors but all possibly self-controlled behaviors, is the Theory of Planned Behavior (TPB) from the social psychologists Ajzen (Ajzen, 1985; Ajzen, 1991). With the lens of this model, behavioral success depends on motivation (behavioral intention) and the ability (behavioral control); it includes three tenets toward the specific behavior: attitudes, social norms and perceived control of the behavior. Also, this model has its limitations and is not comprehensive to account for all factors influencing behavior, for example, emotions or economic factors. However, it has been applied in different areas to understand human decision-making process and behavior and has become prominent to study pro-environmental behavior during the past decades (Han, 2021; Liobikiene et al., 2016; Yuriev et al., 2020). Pro-environmental behavior can be broadly defined as the “behaviour that consciously seeks to minimize the negative impact of one’s actions on the natural and built world’ (Kollmuss and Agyeman, 2002). Comparison of results is somewhat difficult, as the TPB model has not been used consistently, but with modifications and adaptations often missing to report the explained variance by the included constructs (Yuriev et al., 2020). For example, Liobikiene et al. revealed that subjective norm had the highest influence on green purchase behavior across 27 European countries followed by the interaction of knowledge and confidence (Liobikiene et al., 2016). On the other hand, Heeren et al. could show that rather perceived control of one’s behavior than knowledge about sustainability itself was a strong predictor for sustainability-related behavior (Heeren et al., 2016). The authors concluded that, if sustainable behavior is the goal, one should rather focus on educating students about how to engage in those behaviors rather than transferring knowledge on sustainability in general. Another example, findings from a study on waste prevention and travel behavior from Cogut et al. (2019) pointed out that the link between awareness and behavior varies and is behavior-specific. The authors stressed the importance of not taking a one-size-fits-all approach (Cogut et al., 2019). The gap between having knowledge as well environmental awareness and the actual lived pro-environmental behavior is still less understood. Indeed, a person-centered approach seems to be necessary to understand driving forces for pro-environmental behaviors. Further, little is known about ESD approaches that consider this need for individualism and how they impact on transforming behavior.

The aim of this study was to explore students’ learning outcomes in relation to SD key competencies and to deepen understanding of the facilitators and barriers experienced during pro-environmental behavior change using an EL approach. First, the course task, designed within the EL framework, is presented as part of a bachelor’s program in Health Promotion. Second, students’ individually chosen pro-environmental behavior change is described, along with their reflections on the process and factors contributing to (un-) success. Finally, students’ new insights and understanding critical for SD are outlined, together with other observed effects of the EL approach.

Despite advancements in higher education that have successfully enhanced knowledge, awareness, critical and systems thinking, and integrated problem-solving, there remains limited understanding of how to effectively address pro-environmental behavior through education. The aspect of self-awareness and behavior change has often been overlooked. The present study aims to bridge this gap by presenting a promising educational approach and the learning effects, focusing on one of the core elements of SD – transforming human behavior.

In the following, the contextual frame of the course will be briefly described, followed by an overview of course content with a detailed description of the specific part that focuses on individual behavior change.

EL was introduced by psychologist and educational theorist David Kolb (1984) and presents a robust framework for understanding how individuals acquire and apply knowledge through a dynamic process. Kolb’s model builds on earlier psychological theories, notably the work of John Dewey, Kurt Lewin, and Jean Piaget, synthesizing their views into a more comprehensive approach that focuses on the experiential dimension of learning. There are three principles of EL:

1. learning as a process instead of outcome (it is a dynamic, ongoing and iterative process, in which experiences shape knowledge, which is tested and refined through further experiences);

2. learning is grounded in experiences (concrete experiences are the basis for observation and reflection, it is most effective when tied to real-world applications and by that emphasize the practical relevance); and

3. learning involves the resolution of contradictions (learning requires the resolution of conflicts between dialectically opposed modes of adaptation to the world) (Kolb, 1984).

This cyclical process allows for continuous learning and development, where the learner is always engaged in an active process of doing, reflecting, conceptualizing, and testing. Kolb’s ELT has been widely adopted across disciplines, particularly in education, quality management, and health sciences, due to its applicability in real-world contexts. Empirical research, including meta-analyses, supports the positive impact of EL on educational outcomes. For instance, a study by Burch et al. (2019) confirmed that EL significantly enhances students’ academic performance and fosters superior learning outcomes. EL can be considered a promising method to facilitate advanced learning and induce behavioral changes, which are crucial for SD (UNESCO, 2014).

The task of a two-week test of pro-environmental behavior change is embedded in a first-level course on SD within a bachelor’s program in Health Promotion. In 2016, the Secretary General of the United Nations stated at the opening of the 9th Global Conference on Health Promotion in Shanghai that:

Health promotion and SD seem to be inevitably intertwined and the relation between SD and health promotion goals has been discussed and conceptualized by several authors (Buse and Hawkes, 2015; Schmidt et al., 2015; Spencer et al., 2019). Both phenomena imply the need for system thinking, including the understanding of the interconnection of individual behavior and a wide range of social and environmental interventions and practices. From this biopsychosocial-ecological perspective, determinants of health are as well determinants of SD, they are manifold, complex and the way they interact even “wicked” (Brundiers and Wiek, 2013; Hull et al., 2018).

The task is structured as follows: students are required to modify a self-selected behavior to align more closely with a sustainable lifestyle over a two-week period. The activity begins with a reflective analysis of their current behavior and its impact on the three dimensions of SD: ecological, economic, and social. Students must then identify a specific behavior that, if altered, would contribute positively to SD, as substantiated by relevant literature and by using a systems-thinking approach (pertaining to any or multiple dimensions of SD). To facilitate an understanding of the underlying causes of their behavior, the Ishikawa diagram is introduced (see Figure 1). Also known as the fishbone diagram due to its resemblance to a fish skeleton, this tool was developed by Kaoru Ishikawa in the 1960s and has been widely applied in quality management (Ishikawa, 1985). Embedded in principles of root cause analysis, the Ishikawa diagram is designed to systematically identify and visualize multiple contributing factors to a given issue or inefficiency – in this case, an unsustainable or suboptimal behavior. By mapping causal relationships, this method supports a holistic and structured approach to problem-solving, enabling students to recognize key determinants influencing their behavior.

To plan the individual improvement process, students are introduced to Langley and Nolan’s model for improvement (Langley et al., 2009). The model for improvement was developed by associates in process improvement with its roots in quality management and organizational performance. The model comprises three basic questions and a fourth element that describes a cycle for testing innovations and can be closely related to Kolb’s learning cycle (see Figure 2). The first three questions about “What are we trying to accomplish?”, “How will we know that a change is an improvement?” and “What change can we make that will result in improvement?” help students to reflect on their behavior itself, how it looks like now and where do they “want to go” (anticipatory) and to decide what behavior is wanted to be changed. Students have full autonomy in choosing which behavior to modify, provided they can substantiate its relevance to a more sustainable lifestyle based on existing literature. There are no constraints regarding the scale of the change in terms of its potential impact on SD, nor is success a requirement – rather, the emphasis is on engaging with the process and attempting meaningful change.

Once students have determined the behavior they wish to change and established a method for measuring it, the next step is to integrate this change into their daily lives. This process involves systematically planning and testing the modification, observing its effects, and documenting both expected and unexpected outcomes on a daily basis. This approach aligns with the fourth component of the Model for Improvement, known as the Plan–Do–Study–Act (PDSA) cycle (see Figure 2). It also corresponds with Kolb’s EL cycle, which comprises four stages: concrete experience, reflective observation, abstract conceptualization, and active experimentation (Kolb, 1984). Over a two-week period, students implement the planned behavioral change (Do). They are required to document their daily progress, including successes and setbacks, facilitating and inhibiting factors, emotional responses and any additional observed effects.

At the conclusion of the intervention, students must compile a final report. This report should include an analysis of the collected data, a critical reflection on their findings, and a discussion of the results (study). Finally, students are expected to evaluate their learning process and outline their intentions for future actions (act).

Students’ anonymous reports were analyzed by the means of thematic content-analysis with the following themes: chosen behavior change, perceived facilitators and barriers for change, plans for continuous behavior change and new insights and understandings of students. Following the concept of purposive sampling, reports included in the analysis were from the second and fourth year the course was running (2016 and 2018). Students from these two years were asked and had given informed consent for this study. The analysis was done in NVivo (12.2.0) software that supports qualitative and mixed methods research. Reports were read and text were systematically structured to the themes. Within each theme, sub-themes were identified, and meaningful units were coded following the principles of summative content analysis (Hsieh and Shannon, 2005).

The study has been carefully designed to safeguard any ethical issues. Students were informed and gave verbal informed consent for the study. Reports were uploaded anonymous and individual names were replaced by numbers; no individual can be identified. Focus is not on sensitive personal data as defined by the Swedish Personal data act but on individuals’ learning.

In total, reports from 39 students (19 from year 2016, 20 from year 2018, female: n = 26, male: n = 13) were analyzed. The reports were written in Swedish, all citations in the following results were translated from Swedish into English by Google Translate (www.translate.google.com).

Table 1 gives an overview of the behavior chosen, the success of changing the behavior and plans of continuing. Four domains of behavior could be identified: most students chose to change their food habits, e.g. ecological products or less meat consumption (39%), followed by increasing physical activity, i.e. less car driving, active transport or training (28%), saving resources (e.g. recycling or less consumptions, 20%) and decreasing screen-time (13%).

Most of those who tried to change food habits and those who started to recycle or reduce their consumption in general succeeded completely (80%, respectively 75%). Most of those who chose to reduce their screen time succeeded partly (80%). Almost all except of three students (92%) planned to continue somehow with their change.

Figure 3 describes quantitative the coded barriers (as well as facilitators) grouped by the four domains of behavior. Overall, nine barriers were recognized that could be divided into internal, those that can be influenced by the person themselves (n = 5) and external factors, those that cannot be controlled by the person themselves (n = 4). The latter were about climate and weather, social norms, security and lack of alternatives whereas internal barriers were about laziness/lack of motivation, lack of time or stress, sickness, absence of strategy or planning and economy. Barriers were behavior specific. For example, bad weather and sickness hampered only to be more physical active named of two students:

Another physical activity specific hinder was the experienced unsafety of a physical place as expressed by two students:

Examples for food habits and saving resources specific barriers were lack of alternatives expressed by the two students as:

Common and more general barriers that could be found in at least three out of four behaviors were laziness/lack of motivation, lack of time and stress, absence of strategy or planning and social factors. Social factors could be expressed differently:

The identified facilitators stratified by the four behavior domains can be found in Figure 2. Overall, eight facilitators were identified, five internal and three external factors. The latter were social factors, climate/weather (both were also named as barriers), and accessibility, whereas internal facilitators were attitude and motivation, strategy and good planning, knowledge and understanding, small changes and economy. Common facilitators for at least in three behavior domains were strategy and good planning as well as the accurate attitude and motivation. Knowledge and understanding were particularly boosting a more sustainable food consumption. Two students wrote as following:

Social factors were enabling for increased physical activity and sustainable food, and expressed as following:

Accessibility facilitated physical activity and recycling:

The insight of economical savings, if active transportation is used instead of car or if less meat is bought was also enabling for these behaviors.

New insights and understanding gained and expressed by the students could be categorized in three major themes, namely, system thinking, behavior change, SD. All students independently of the chosen behavior change gained new insights in all three areas. To understand the interconnection between things and system thinking was expressed as following:

Beside system thinking, students also increased their understanding on behavior change. Some students got insights in their own lifestyle “I became aware of the automatic tendencies I have to constantly use the phone, and how much time it actually takes”, but also how difficult it is to change a behavior “The project opened my eyes on […]. how powerful the power of the habit is”. Further, students got a better understanding how to facilitate behavior change:

Above that, students learned that reasons not to do a specific habit could be switched into reasons to do it:

Finally, they were able to reject their prejudices: “It was easier to eat vegan than I thought”.

Beside system thinking and insights on behavior change, students gained insights in sustainability and the need for SD. As one student wrote “Sustainable development is difficult. It is terribly complex and wide”. Another student expressed it as following “For my part, this project was an aha experience and a kind of awakening how we waste the earth’s resources”. Awareness was raised among students not only on the need for change but also how to do some change:

Finally, but not least, students experienced proudness to contribute to SD that gave them motivation to continue their behavior change:

Another student expressed it as:

Some other effects named in students report were about an increased health and well-being not only through physical activity but also through vegetarian food and less screen-time. Further, economical savings by active transport or less meat purchases were named. In some cases, the behavior change project got a domino-effect. Students challenged their social environment family and friends, discussions were started and in some cases behavior changes were done together: “The result turned out that almost everyone in the family was happy and liked the vegetarian food”, or as another student wrote:

The study examined the impact of an innovative educational approach on students’ learning for SD in which students actively modified a self-selected behavior to promote a more sustainable lifestyle. This approach was grounded in the principles of EL. Chosen pro-environmental behavior ranged from increased physical activity and active transportation, sustainable food choices, saving resources to reduction of screen-time. Almost all students expressed plans to continue somehow with their tested “new” behavior beyond the project time. Their reflections showed distinctly novel insight and understanding not only on SD but also on their individual behavior in relation to SD, and on making behavior change happens. This kind of active transformative learning process created deep learning as characterized by critical thinking and understanding underlying meaning (Biggs and Tang, 2007).

The present SD course integrated both theoretical knowledge and applied learning, covering not only SD topics themselves, but also systems thinking (enhancing awareness of interconnections), learning processes, the complexity of health and well-being, and models of behavioral change. Through an EL approach, students were required to actively apply their acquired knowledge across these domains by implementing and analyzing a self-selected behavioral change over a two-week period. They were further expected to critically evaluate and articulate the relationship between their chosen behavior and SD While the course provided a foundation of general principles, the EL approach emphasized an individualized and person-centered learning experience. By balancing self-awareness with perceived control over their behavioral change, students had the autonomy to select both the specific behavior they wished to modify and the extent of the change. Individualization and perceived behavioral control have previously been identified as critical factors in effectively facilitating behavioral learning outcomes (Cogut et al., 2019; Heeren et al., 2016).

Our findings indicate that the EL approach could address all eight key competencies for ESD, enhancing beyond cognitive and socio-emotional as well behavioral learning outcomes. Since students were asked to identify personal behaviors for improvement in relation to SD, they were forced to reflect on their own role in community and society (self-awareness) and understanding interconnectedness (system thinking). As Tyler already wrote in the year 1949 – as the precursor for Kolbs’ EL theory – “learning takes place through the active behavior of the student: it is what he does that he learns” (Tyler, 1949). The behavior change project offers the students a real-world learning experience that focuses on their own actions and choices by building cognitive structures through engagement with experiences. To foster meaningful learning experiences and intrinsic motivation, students were given autonomy in selecting both the specific behavior to modify and the extent of the change. This approach aligns with learner-driven pedagogy, in which students initiate and direct their own actions, leading to sustained engagement and further behavioral adaptation (Herranen et al., 2018). Consistent with this approach, our findings indicate that students were motivated to maintain their newly adopted behaviors beyond the project duration.

By using the fishbone diagram to identify the causes of their current behaviors, alongside observing and documenting facilitators, barriers, emotions, and other effects during behavior change implementation, students reflected on both internal (personal) and external (e.g. family and peer) norms and values, as well as contextual factors. They questioned the identified norms and opinions and started actively to take a position in SD by initiating discussions with their families and friends about their thinking and actions. Beyond critical thinking competency, this process facilitated the development of both normative and systems thinking competencies. Students enhanced their ability to recognize and understand causal relationships and the complexity of systems, particularly as they reflected on the connections between their behaviors and various dimensions of SD Through this, they further developed anticipatory competency by evaluating the potential consequences of their actions and formulating personal visions for the future.

The discussions students engaged in, both privately and within the active learning classroom at university, contributed to the development of their collaboration competency. Through the process of presenting and providing feedback on their planned behavior changes, including the fishbone diagram, students learned from others and developed an understanding of, and respect for, diverse needs, perspectives, and actions. Furthermore, students began to collaboratively develop, plan, and implement their behavior changes, particularly when choosing shared areas of focus, such as increasing vegetarian food consumption, while involving their families and peers in the process (strategic competency). This experience enhanced their awareness of the importance of planning and strategic approaches for effective behavior change. Additionally, students gained a deeper understanding that there is no singular solution to a given problem; they recognized the necessity of employing various strategies to successfully achieve behavior change (integrated problem-solving competency).

In addition to its impact on learning for SD, the findings of the present study demonstrated that facilitators and barriers for pro-environmental behaviors varied and were behavior-specific. However, strategy and effective planning emerged as universal facilitators for the successful implementation of all behavior changes, while the absence of strategy or planning was consistently identified as a barrier. These findings align with behavior change research in healthcare (e.g. preventive medicine), where action planning and goal-setting are established as critical components (Cole et al., 2023; Peng et al., 2024). Action planning has been shown to mediate the intention-behavior relationship, thereby increasing the likelihood that intentions will translate into actual behavior change (Cole et al., 2023; Schwarzer et al., 2011). Furthermore, incorporating a coping plan—focusing on potential barriers, strategies to enhance facilitators, and refining the action plan – can further strengthen preparedness and resilience in the face of unforeseen challenges, enhancing the likelihood of sustained behavior change (Schwarzer et al., 2011). This approach aligns with behavioral models such as the Theory of Planned Behavior, which emphasizes the importance of perceived control – strengthened through thoughtful planning – in effectively translating intentions into actions (Ajzen, 1991).

Motivation, another key determinant of behavior changes and a component of the TPB, emerged in this study as a critical factor influencing the success or failure of pro-environmental behavior change, depending on its presence or absence. In healthcare interventions, strategies such as motivational interviewing are commonly used to enhance motivation and facilitate behavior change (Natanek et al., 2023; Rubak et al., 2005). However, in the present study, students received support primarily through reflective discussions with their peers.

Behavior changes related to adopting more climate-friendly diets were influenced by increased knowledge and understanding of environmental impacts, as well as accessibility to alternative food options, particularly when eating outside. Deslippe et al.’s (2023) systematic review on lifestyle interventions reported similar knowledge and understanding as common facilitators, which additionally identified a lack of time on the other hand as a common barrier – a result corroborated by the present study. Further, insufficient social support was specifically hindering behavior changes related to dietary adjustments, recycling, and screen-time reduction, while social network engagement and commitment emerged as key facilitators for promoting physical activity changes. These findings are consistent with those reported by Deslippe et al. (2023).

The present study is a case description of how the EL method can enhance deep learning for SD In line with Marton and Booth’s framework, which categorizes learning into six successive levels - culminating in “changing as a human” and “changing behavior” as the highest stage – the students experienced this transformation (Marton and Booth, 1997). However, there is a risk that this change may be temporary, occurring only within the context of the course, with the possibility of relapse. While all but three students expressed their intention to maintain their behavior change to some extent, a follow-up study one year later could have provided deeper insights into the long-term effectiveness of the change.

Furthermore, there is a potential risk of social desirability bias, as the reported behavior change was self-assessed. Clearly stating in the assignment that success was not the primary outcome, but rather the experience of change – including facilitators and barriers – could have mitigated the risk of students overstating their success. Additionally, the behavior change process took place within the course framework, which included regular workshops and continuous status meetings, potentially surveilling the students in their transformation. Moreover, the collective experience of behavior change among peers in the class fostered a form of action-learning network, which might have amplified the impact of the EL approach.

This case study, involving 39 students, does not aim to generalize results on behavior change strategies. Instead, it highlights the impact of the EL approach on self-awareness and behavioral transformation for SD. While the identified barriers and facilitators were largely individual and dependent on the specific behaviors chosen, some overarching themes emerged, many of which align with existing literature.

In summary, the described EL approach to pro-environmental behavior change significantly enhanced students’ understanding and insight while fostering the development of all eight key competencies for SD Compared to other research on ESD, this EL approach particularly stimulated the self-awareness competency within systems thinking and action-oriented change. Additionally, the findings indicate that students not only gained new insights and understanding but also underwent personal transformation, expressing a desire to maintain their “new” behaviors. By actively engaging in behavior change, students reduced the psychological and practical barriers to continuing these actions. Moreover, they acquired strategies and a deeper understanding of the critical factors required to facilitate and sustain meaningful change. By emphasizing the importance of self-awareness and individualized approaches, the findings contribute to a deeper understanding of how the EL approach could drive pro-environmental behavior change. While this research underscores the necessity of integrating behavioral transformation into ESD frameworks, the question of how this can be effectively achieved requires further exploration. Future research should focus on developing innovative educational and teaching methods within a whole-institution approach, incorporating follow-up data collection at multiple time points to ensure lasting change.

The author would like to thank Arjen E.J. Wals for reviewing the initial manuscript and providing valuable feedback to improve it.