Using motivational interviewing to promote teacher efficacy, autonomy-supportive teaching and students’ academic motivation

Abstract

Motivational interviewing (MI) is a collaborative communication style used to promote individuals’ motivation, and there is growing support for using MI in schools. This study aims to test whether a teacher-focused intervention program based on MI and autonomy-supportive teaching increases teachers’ autonomy-supportive teaching, teacher efficacy and students’ academic motivation and perceptions of autonomy support. In this intervention study with a short-term longitudinal design, teachers were trained in MI and autonomy-supportive teaching style, along with a control group in which the students’ teachers did not receive specific training. 14 teachers and 478 students (10–12 years) participated in the study. The MI-based intervention were found to significantly increase teachers’ perceived autonomy-supportive teaching and sense of efficacy in student engagement, instructional strategies, and classroom management from Time 1 to Time 2. However, the intervention did not increase students’ academic motivation or perceptions of teacher autonomy support over time. The current study indicate that school-based MI may be more important for teachers’ professional development than for younger students’ academic motivation. This study demonstrates that MI training can have an impact on teachers’ instructional behaviors and increase teacher efficacy, providing valuable insights for both teacher education and school leaders.

Keywords:

• Autonomy support
• motivational interviewing
• professional development
• self-determination theory
• students’ motivation
• teacher efficacy

1. Introduction

Over the last two decades, there has been a considerable increase in research on the importance of teacher-student relationships and on the impact of teachers’ instructional styles on student academic outcomes (Hattie, 2009; Roorda et al., 2017). A significant body of literature has confirmed that teacher support and teacher efficacy influence students’ academic motivation, achievement and engagement in school (Kim & Seo, 2018; Roorda et al., 2011; Tao et al., 2022). However, previous research has suggested that teacher education may not sufficiently prepare teachers to build positive teacher-student relationships (Korpershoek et al., 2016; Rucinski et al., 2018). Furthermore, teachers and pre-service teachers have described relational work with students as the most difficult part of their profession (Jensen et al., 2015). Recently, Motivational interviewing (MI) has been used in schools (Rollnick et al., 2016; Strait et al., 2014) to help teachers develop and strengthen their relational competence and instructional style. MI is an evidence-based collaborative communication style used to promote individuals own motivation for change (Magill et al., 2018; Miller & Rollnick, 2013). The approach is respectful of the individual’s autonomy (self-determination) and promotes collaborative relationships. MI has been applied in schools in two different ways: student-focused school-based MI and consultative school-based MI (Rollnick et al., 2016; Strait et al., 2014). The student-focused type of MI has been used directly with students to improve both academic and mental health outcomes (Snape & Atkinson, 2016). The consultative type of MI, on the other hand, has been used with teachers and parents to either promote students’ academic performance or prevent challenging behaviors (Frey et al., 2011, 2013). There has also been a growing interest in promoting autonomy-supportive intervention programs in schools, based on self-determination theory (SDT; Deci & Ryan, 2000), in order to develop teachers’ instructional style and to increase students’ academic motivation (Reeve & Cheon, 2021). Ryan and Deci (2020) stressed that such intervention studies are important for demonstrating the practical value of motivational research; however, there is a lack of research in which school-based MI and autonomy-supportive intervention programs are combined and implemented in school settings. Hence, this study aims to test whether a teacher-focused intervention based on MI and autonomy-supportive teaching can increase teachers’ autonomy-supportive behaviors and teacher efficacy, and increase students’ academic motivation and perceptions of autonomy support.

2. Theoretical perspective

Markland et al. (2005) suggested that SDT can be used as a theoretical framework when explaining the effects of MI, in other words, why MI works. Although MI is a collection of communication techniques, it is in many ways similar to SDT, and autonomy support is central for both approaches (Deci & Ryan, 2012). In this section, we first contextualize our work with reference to SDT and MI more broadly and briefly outline the core elements and principles that underpin SDT and MI. Finally, we consider what is known about school-based MI and autonomy-supportive interventions in school settings.

2.1. Students’ academic motivation

Previous longitudinal studies have shown that students’ academic motivation decline between grades (Lepper et al., 2005; Otis et al., 2005) and students’ autonomous motivation also tends to decrease within the academic year, from fall to spring (Cohen et al., 2022; Corpus et al., 2009; Opdenakker et al., 2012). SDT is a broad theory about human motivation and development, and we use it as a relevant theoretical framework to understand academic motivation (Deci & Ryan, 2000; Ryan & Deci, 2017). Furthermore, SDT distinguishes between controlled motivation and autonomous motivation and suggests that there are different types of regulated motivation: intrinsic, extrinsic and amotivation. When behaviors are regulated by intrinsic motivation, students experience an inherent joy or satisfaction in the self-chosen activity and perform activities and tasks for their own sake. If behaviors are regulated by extrinsic motivation, students primarily perform activities in order to satisfy others, to receive some form of social or material reward or because they were coerced to do so. According to SDT, extrinsic motivation can in turn be divided into four subtypes of regulated motivation: external, introjected, identificated and integrated regulation. External regulation is regarded as a controlled form of motivation, in which behaviors or activities are performed through external rewards or punishments. Introjected regulation refers to extrinsic motivation that has been partly internalized. The activity or behavior is not completely self-chosen, and students may perform tasks to avoid guilt, anxiety or in fear of failure. In identified regulation, activities are self-chosen and considered important. The student identifies the value of the activity, but the activity is still not perceived as fun or engaging. Integrated regulation is the most autonomous form of extrinsic motivation, in which behaviors and activities are in line with students’ own values and interests. The absence of motivation, amotivation, can result from a lack of perceived competence or from a lack of interest and value. A student may feel that he or she cannot control or influence the situation or sees no point in participating in the activity (Deci & Ryan, 2000; Ryan & Deci, 2020). SDT emphasizes the importance of not controlling the students and suggests that students who are autonomously motivated are more engaged, effective and persistent compared to students who feel controlled (Ryan & Deci, 2017).

2.2. Core elements of Motivational Interviewing (MI)

MI is based on an underlying foundation called the MI spirit, which is based on four aspects: partnership, compassion, evocation of change talk and acceptance (Miller & Rollnick, 2013). The first aspect, partnership, refers to the creation of a relationship and active collaboration between the student and the MI practitioner. The second aspect, compassion, means that the MI practitioner strives to promote the student’s wellbeing. The third aspect, evocation, is based on the notion that the student has internal resources and that the MI practitioner’s task is to evoke these resources. The final aspect, acceptance, concerns empathy and respecting the student’s autonomy. The ability to convey empathy has proven to be of great importance for creating a positive conversational climate, and empathy has proven to be a prerequisite in the work of evoking motivation for behavior change (Miller & Rollnick, 2013; Rollnick et al., 2016). MI is also based on four processes that interact with each other: engaging, focusing, evoking change talk, and planning for change. According to Miller and Rollnick (2013), the engaging process involves a relationship-building foundation in which the MI practitioner creates a relationship and collaboration with the student. In the focusing process, the conversation is guided in a specific direction based on the student’s needs and wishes. The evoking process involves evoking the student’s own motivation for change. This is done by trying to evoke change talk (i.e., the student’s own statements of will, need, desire or reasons for change). The fourth process, the planning process, aims to formulate concrete goals and increase the student’s readiness for change (Miller & Rollnick, 2013; Rollnick et al., 2016). There are four core skills used throughout MI. These can be seen as tools used to navigate the conversation: open-ended questions, affirmations, reflections and summaries (OARS). Open-ended questions explore the student’s experiences and perspectives, and give the student more space to provide answers that are more detailed. By giving the student a feeling of being seen and understood, affirmations strengthen the student’s self-efficacy. Affirmations are also important for eliciting change talk (Apodaca et al., 2016). Reflections are statements that reflect what the student has said, which is a central part of MI. In addition, reflections are a way for the MI practitioner to reinforce certain things that the student says and to show active listening. Summaries can provide an overview of the conversation, as the MI practitioner emphasizes certain parts of the conversation (i.e., by reflecting back). Summaries also fulfil a pedagogical function, as parts of the conversation are repeated. Within MI, the MI practitioner avoids giving direct advice. The practitioner instead asks for permission to provide information, which is a way to show respect for the student’s autonomy (Miller & Rollnick, 2013).

2.3. MI in educational settings

The consultative type of MI has been used with teachers and parents in order to help them promote students’ academic performance or prevent challenging behaviors (Frey et al., 2011, 2013). A qualitative study (Svensson et al., 2021) showed that teachers who were trained in MI experienced MI facilitating their relational work with both students and parents. Teachers considered that MI helped them become more autonomy-supportive than before, and MI provided relational skills that they wished they had acquired earlier in their profession. However, Small et al. (2014) highlighted that implementing MI training in school environments can be challenging due to the limited time teachers may have for professional development. Regarding student-focused MI, previous research has shown that MI has positive effects on students’ confidence in their own ability, school attendance and attitudes towards school (Atkinson & Woods, 2003; Cryer & Atkinson, 2015; Sheftel et al., 2014). Snape and Atkinson (2016) conducted a literature review on student-focused MI, in which seven studies reported positive effects on students’ academic outcomes. For example, middle school students had significantly higher mathematics grades and self-reported positive academic behavior after a single MI session (Strait et al., 2012; Terry et al., 2013).

Classroom-based MI have been used in groups to promote undergraduate students’ motivation to study before exams (Reich et al., 2015; Strait et al., 2019). The findings show that undergraduate students who participated in a MI-based intervention showed significant improvements in post-intervention exam grades compared to students who did not participate in the intervention (Reich et al., 2015). One limitation of this study is that Reich et al. (2015) did not have a randomly assigned control group. Instead, they used grade data from students from the previous semester as a control group. In the intervention group, all the students participated voluntarily, but the students in the control group did not. The results from the control group may therefore have looked different if it had only been students who voluntarily wanted to participate. Due to the limitations of that study, Strait et al. (2019) conducted an intervention study with a randomly assigned control group. The students in the intervention group participated in a 15–20-minute MI intervention, while the students in the control group only received a handout on study strategies. The results showed no significant differences in test performance between the intervention group and the control group. Strait et al. (2019) discussed whether giving students handouts on study strategies may be as effective as using a classroom-based MI to promote academic achievement. Given the various results of the presented studies, more research on classroom-based MI is needed wherein a control group is included and the intervention lasts for an entire school year.

In summary, in most previous studies concerning school-based MI, other professionals (e.g., school psychologists or clinical psychology graduate students) have delivered MI to the students, not the teachers themselves. Hence, there is a need for more research on school-based MI where teachers are trained in MI specifically to apply MI with their students. It is valuable to examine what effects such teacher-focused interventions may have on students’ academic motivation, teachers’ instructional style and teacher efficacy (i.e., teachers’ belief in their own capability to organize and implement specific teaching tasks required to achieve the desired outcomes of student engagement and learning; Tschannen-Moran & Hoy, 2001).

2.4. Autonomy-supportive interventions in schools

The contention that autonomous motivation and autonomy support is critical to an individual’s long-term engagement in an activity is central to both MI and SDT. However, in MI, supporting individuals’ autonomy refers to a way of being with people. Within SDT, autonomy support refers more to certain autonomy-supportive behaviors. Research on SDT-based autonomy-supportive interventions in schools has increased in the last two decades, where teachers have been trained in using an autonomy-supportive teaching style (Reeve & Cheon, 2021). Previous studies have identified teacher autonomy support as being provided by a number of specific autonomy-supportive instructional behaviors: by teachers taking students’ perspectives, supporting their intrinsic sources of motivation, giving students choices, showing patience, providing relevant rationales for learning tasks, and minimizing the use of controlling languages (Reeve, 2009; Su & Reeve, 2011). Autonomy-supportive teaching vitalizes students’ psychological needs for autonomy, competence and relatedness. In an autonomy-supportive environment, students are encouraged to come up with their own suggestions and initiatives, and the teacher strengthens the students’ sense of freedom of choice and self-determination (Reeve, 2009; Ryan & Deci, 2017).

A meta-analysis (Su & Reeve, 2011) shows that autonomy-supportive training intervention programs are an effective way to teach teachers how to apply an autonomy-supportive approach and become significantly less controlling towards students. Several previous studies of autonomy-supportive intervention programs with teachers show that students who receive autonomy support from their teacher show positive effects both academically and developmentally; through greater engagement in the school, increased intrinsic motivation, better school results and increased well-being (e.g., Cheon & Reeve, 2013; Cheon et al., 2012, 2019; Reeve et al., 2004). Recently, it has also been demonstrated that an autonomy-supportive intervention program for teachers had a more favorable impact on student outcomes when it combined a web-based and face-to-face approach, as compared to the groups that exclusively utilized either web-based or face-to-face interventions (Tilga et al., 2021). Previous studies have also shown that autonomy-supporting intervention programs can provide teachers greater teacher efficacy, job satisfaction and teaching motivation (Cheon et al., 2014, 2018; Tilga, 2021). These results illustrate that providing autonomy support benefits teachers in much the same way that it benefits their students to receive autonomy support. In summary, these previous studies show that autonomy-supportive intervention programs may have positive effects on students’ and teachers’ motivation and well-being.

3. Purpose

In the present study, we combined MI and the principles of autonomy-supportive teaching in a teacher-focused intervention program, since we believe that the combination of these approaches can foster teachers’ relational approach and strengthen their instructional style. Most previous studies of school-based MI have been carried out with middle and high school students; in these studies, non-teaching professionals (e.g., school psychologists or clinical psychology graduate students) delivered MI to the students. Hence, in our study, we will focus on teachers and school-based MI for younger students (10–12 years). The aims of this study are threefold: (i) to test whether a teacher-focused intervention based on MI and autonomy-supportive teaching can increase teachers’ autonomy-supportive behaviors and teacher efficacy, (ii) to test if the intervention can increase students’ autonomous academic motivation and their perceptions of autonomy support, and (iii) to test if the intervention can decrease students’ controlled academic motivation.

4. Methods

4.1. Design and participants

In the present study, we conducted an intervention study with a short-term longitudinal design (8 months), with an intervention group in which teachers were trained in MI and autonomy-supportive teaching style, along with a control group where the students’ teachers did not receive this specific training. The inclusion criteria were that the teachers should teach in grades 5–6 (student ages 10–12 years) and have had no MI training before. The reason we chose teachers and students in grades 5 and 6 was partly because previous studies have shown that students’ academic motivation decreases as they grow older (Lepper et al., 2005; Wang & Eccles, 2012). Moreover, the teachers needed to have a relationship with the students before the intervention (in the Swedish school system, students usually getting a new teacher in grade 4); thus, these students knew the teacher before the intervention and could have an idea of any changes in the teacher’s behavior. From the beginning, we sought to randomly divide teachers into an intervention group and a control group based on a wait list control design; unfortunately, this was not possible to implement when we had a large number of teachers drop out from the study. At first, 38 teachers had volunteered to participate in the study, but due to COVID-19 and other reasons (e.g., sick leaves, changes in duties), 22 teachers dropped out.

16 teachers participated in the intervention group. The teachers worked at nine different compulsory schools in the middle of Sweden. All participants in the sample were women (M = 47.5 years, SD = 6.9; range = 36 to 58) who had an average of 16.31 years of teaching experience (SD = 8.2; range = 2 to 30). They taught different subjects in grades 5–6 (e.g., mathematics, Swedish, art, English, history, civics). The teachers received MI training with a focus on school settings and a short introduction to the principles in autonomy-supportive teaching, delivered in five workshops during one semester. A sample of 478 students (51% boys and 49% girls) in grades 5 (54.6%) and 6 (45.4%) at 16 Swedish compulsory schools participated in the study. The students in the intervention group (n = 291) consisted of 53% boys and 47% girls and were located in 22 classes (43% in grade 5 and 57% in grade 6) at nine different schools (seven K-6 schools, one K-9 school and one 4–9 school). The students in the control group (n = 187) consisted of 49% boys and 51% girls and were in 13 classes (73% in grade 5 and 27% in grade 6) at nine different schools in the same county (eight K-6 schools and one K-9 school). The schools were diverse in terms of geographical location and size.

We had originally planned for a control group of teachers; however, since only eight teachers participated in the control group and only answered the survey at baseline, despite being given several reminders via email, we decided not to include this group in the study.

4.2. Ethical considerations

After receiving ethical approval from the Swedish Ethical Review Authority (ref. 2020–00744) we invited teachers and students to participate in the study. The first contact was made via email with school principals at Swedish municipal compulsory schools in one county in the middle of Sweden. Principals passed on an information letter to teachers, where the teachers were asked to contact the first author if they were interested in taking part in the intervention and study. The letter provided information about the purpose and procedures of the study, how data would be processed, the voluntary nature of the study and the right to withdraw consent at any time. Written informed consent was digitally obtained from the participants before they answered the questionnaire. The students of the participating teachers were asked to participate in the study. An information letter to their guardians as well as a consent form were distributed with help from class teachers. The guardians provided written consent for their children to participate in the study. The students also received information about the study from their teachers before the data collection was carried out. At the time of the survey, the students received both written and oral information about the voluntary nature of the study and about their right to withdraw their consent at any time. Informed consent was obtained digitally from the students when they answered the questionnaire using a web-based survey tool.

For the control group, an email was sent out to all municipal compulsory schools in the same county as the intervention group. This email contained information about the study and the principals were asked if there were teachers and classes in grades 5–6 that might want to participate in the study. The principals passed on the question and an information letter to the class teachers in grades 5–6. Information letters to students and guardians, and consent forms, were distributed with the help of class teachers in the same way as in the intervention group, and consent was obtained in the same manner for both groups.

4.3. The intervention

Teachers received MI training with a focus on school settings. The MI training was delivered in five workshops (2.5 hours per session) during a single semester (Autumn 2020). The first four workshops were held in a conference room at a school, but the last workshop was held digitally via Zoom due to the increased spread of Covid-19. The MI training was based on recommendations from the Motivational Interviewing Network of Trainers (MINT) and previous research on effective strategies for training in MI (Miller & Moyers, 2006). The MI training was delivered by the first author, who is formally trained in MI and has many years of practical experience, and by a psychologist who is a member of MINT and who has about 10 years of experience as an MI trainer. The workshops introduced the core elements and skills of MI, facilitated the development of the relational aspects, and provided an understanding of the practical application of school-based MI. The workshops included the following: (1) understanding the MI spirit and the core MI skills (open-ended questions, affirmations, reflections and summaries), (2) understanding the processes in MI and evoking change talk, (3) evoking readiness for change and learning MI strategies for dealing with resistance, (4) learning and understanding the instructional behaviors of autonomy-supportive teaching (based on SDT), (5) discussing the successes or challenges of the implementation, and encoding audio-recorded authentic MI sessions. During the workshops, several teaching methods were used, including lectures, group discussions, role-play, and modelling. Between each workshop, the teachers were given practical exercises to apply MI in their classrooms, as a part of the skills training. Before the final workshop, the teachers were to audio-record an authentic MI session with one of their students and transcribe the recording verbatim. At the final workshop, an encoding of the teachers’ recorded sessions was made in order to gain better insight into how MI was applied. According to Su and Reeve (2011), intervention programs focusing more on skills-based training are more effective than programs that mainly focus on knowledge-based training.

Teachers’ attendance during the workshops varied, mostly due to the risk of infection in connection with covid-19. At the first workshop, there were 15 participants, and one teacher was absent. All 16 teachers attended the second and third workshop. At the fourth workshop, there were 14 participants. At the last workshop, there were 13 participants. After each workshop, extra follow-up meetings were offered digitally via Zoom the following week for those who had been absent, but not everyone had the opportunity to participate in these extra workshops. Everyone received printed handouts after each workshop via email.

4.4. Measures

4.4.1. Teachers’ measures

Previously validated measures were used to collect survey data. To assess self-rated autonomy support, teachers completed the 6-item teacher version of the Learning Climate Questionnaire (LCQ) (Black & Deci, 2000; Cheon et al., 2016) (e.g., “I provide my students with choices and options”), rated on a four-point Likert-type scale ranging from 1 (strongly disagree) to 4 (strongly agree). To assess self-reported teacher efficacy, we used a back-translated English to Swedish version of the Teachers’ Sense of Efficacy Scale (Tschannen-Moran & Hoy, 2001), the 24-item form (e.g., “How much can you do to motivate students who show low interest in school work?”), rated on a nine-point Likert scale ranging from 1 (nothing) to 9 (a great deal). Teacher efficacy was measured by perceived efficacy in (i) student engagement, (ii) efficacy in using instructional strategies and (iii) efficacy in classroom management. The background variables stated in the questionnaire were gender, number of years in the teaching profession and in which grade they taught. The questionnaire was pilot tested, and three teachers responded to the questionnaire and gave their views on the wording and content of the questions. After the pilot test, some wordings were reformulated since it caused some confusions and could be interpreted in several ways. After these adjustments, the questionnaire was pilot tested again with three other teachers. Thereafter, further linguistic adjustments were made before handing out the final version of the questionnaire.

4.4.2. Students’ measures

Previously validated measures, based on SDT, were used to collect survey data. To assess perceived autonomy support, students completed the Learning Climate Questionnaire (Black & Deci, 2000; Williams & Deci, 1996) (e.g., “I feel that my teacher provides me choices and options”) rated on a four-point Likert-type scale ranging from 1 (never) to 4 (always). The original is actually a seven-point Likert scale, but we chose to modify it a bit by using a four-point scale instead given the age of the students, as previous research suggests that questions with more than four possible answers are not optimal for younger students (Ryan & Connell, 1989). To assess self-rated academic motivation, students completed the Academic Self-Regulation Questionnaire (Ryan & Connell, 1989), which concerns the self-regulations of why students perform school activities (i.e. autonomous or controlled motivation), (e.g., “I do my classwork because I want the teacher to think I’m a good student”), rated on a four-point Likert-type scale ranging from 1 (never) to 4 (always). Autonomous motivation was composed of intrinsic and identified regulations, and controlled motivation was composed of external and introjected regulations. There are two versions of this questionnaire: a standard version and a modified version, created for students with learning disabilities (Deci et al., 1992). There are fewer items in the modified version (17 items) than in the standard version. We therefore chose to use the modified version given the age of the students, as younger children typically have a shorter attention span compared to older students (Deci et al., 1992). The background variables given in the questionnaire were gender and grade.

The scales were translated from English to Swedish using back-translation (Brislin, 1970) conducted by a bilingual individual. After that, the Swedish translation was translated back into English. This translation was then translated back into Swedish by another bilingual person to ensure that the translation conforms to the original source (Brislin, 1970). To test the validity of the student questionnaire, it was pilot tested by nine students in grade 5 in the spring of 2020. After the pilot test, several questions were reformulated, as some words were difficult to understand or were misunderstood. After some linguistic adjustments, the questionnaire was pilot tested again with three other students in grade 5. After that, no further adjustments were made.

4.5. Data collection

The study was carried out over a full school year, between September 2020 and May 2021. Teacher data were collected at two times, using a web-based survey tool (Survey & Report). The questionnaire was emailed via a link sent one week before the MI training (n = 16) and one week after the last workshop (n = 14). Student data were collected in three waves, and the intervention group and the control group answered the same questionnaire. The data collection took place in students’ regular classrooms, and they answered the survey using a web-based survey tool on their iPads. At baseline (Time 1), students in the intervention group answered a pre-test (n = 291), a follow-up after the final MI workshop (Time 2: n = 284), and a follow-up after five months to measure the possible long-term effects of the intervention (Time 3: n = 285). At baseline, students in the control group answered a pre-test (n = 187), a follow-up in January 2021 (Time 2: n = 173), and a follow-up in May 2021 (Time 3: n = 187). The procedural timeline for the intervention program and the three waves of data collection appear in Figure 1.

Figure 1. Procedural timeline of the eight-month intervention program with three waves of data collection.

During baseline data collection, the first author was present in all classrooms to explain and clarify if there were any thoughts or ambiguities. During the second measurement period (Time 2), the authors could not be physically present in the schools due to the pandemic and the local spread of infection; however, the first author was present digitally, via Zoom, on a large screen in all classrooms when the students completed the survey. In this way, they were given the opportunity to ask questions regarding the questionnaire. During the third measurement period (Time 3), the authors were not present in the classrooms due to Covid-19. The questionnaire was emailed to the teachers who forwarded the questionnaire to the students, who answered the survey in the classroom. Students who were absent on the day of the survey were given the opportunity to answer the questionnaire a few days after the original survey occasion.

4.6. Data analysis

The collected data was processed and analyzed using the statistical program IBM SPSS version 27. In order to evaluate the impact of the intervention on teacher outcomes (i.e., perceived autonomy-supportive teaching, perceived teacher efficacy in student engagement, instructional strategies and classroom management), a series of paired samples t-tests were conducted. To analyze student data (perceived autonomy support, autonomous motivation and controlled motivation), we used repeated-measures ANCOVA’s controlling for gender and grade level. The significance level was set to p < .05 throughout.

5. Findings

Descriptive statistics and the results of the paired samples t-tests and repeated-measures ANCOVA’s are presented in Table 1 and Table 2. Teacher data were collected at two times and student data was collected at three times. Only data from teachers who provided both baseline and follow-up data (n = 14) were used in the analysis.

Table 1. Teacher data. Alpha-values, means, standard deviations, t-values and effect sizes for the measured variables at T1 and T2

			Time 1				Time 2
Variables	α	n	M	SD	α	n	M	SD	t	d
Autonomy supportive teaching	.65	14	3.05	0.35	.82	14	3.27	0.35	2.25*	0.62
Teacher efficacy
Student engagement	.78	14	6.13	0.63	.78	14	7.07	0.65	7.20***	1.47
Instructional strategies	.80	14	6.54	0.66	.75	14	7.37	0.63	5.68***	1.29
Classrooms management	.88	14	6.53	0.75	.79	14	7.46	0.58	6.27***	1.39

Notes: *p < .05, ***p < .001. d = Cohen’s d.

Table 2. Student data. Alpha-values, means, standard deviations, F-values and effect sizes for the measured variables

		Intervention group			Control group
Variables	α	n	M	SD	n	M	SD	F	η^2
Autonomy support T1	.88	291	3.20	0.52	187	3.20	0.51
Autonomy support T2	.90	284	3.14	0.53	173	3.02	0.59
Autonomy support T3	.92	285	2.97	0.63	187	2.95	0.67	1.76
Autonomous motivation T1	.80	291	2.65	0.60	187	2.70	0.60
Autonomous motivation T2	.81	284	2.59	0.56	173	2.62	0.64
Autonomous motivation T3	.84	285	2.43	0.62	187	2.46	0.64	3.12*	.007
Controlled motivation T1	.76	291	2.11	0.63	187	1.96	0.59
Controlled motivation T2	.77	284	2.00	0.61	173	1.93	0.53
Controlled motivation T3	.70	285	2.04	0.57	187	1.91	0.52	.30

Notes: *p < .05.

5.1. Teachers’ perceived autonomy-supportive teaching and teacher efficacy

The paired samples t-test showed a significant increase in teachers’ perceived autonomy-supportive teaching from Time 1 to Time 2 (see Table 1), indicating that an MI-based intervention can help teachers become more autonomy-supportive towards their students. Regarding the results concerning the different dimensions of teacher efficacy, a significant increase in teachers’ perceived efficacy in student engagement was shown from Time 1 to Time 2. There was also a significant increase in teachers’ perceived efficacy in instructional strategies from Time 1 to Time 2. Moreover, a significant increase in teachers’ perceived efficacy in classroom management from Time 1 to Time 2 was detected (see Table 1). In summary, our findings indicate that an MI-based intervention can help teachers increase their perceived teacher efficacy in student engagement, instructional strategies, and classroom management.

5.2. Students’ perceived autonomy-supportive teaching

The results showed that the students’ perceived teacher autonomy support was relatively high at baseline (Time 1), in both the intervention group and the control group, but no significant differences were detected (see Table 2). Moreover, neither students in the intervention group nor students in the control group reported any significant change in perceived autonomy support between Time 1 and Time 2. At Time 3, the results did not indicate any significant differences in students’ perceived autonomy support over time, neither in the intervention group nor in the control group.

5.3. Student motivation

Regarding students’ autonomous motivation, both the intervention group and the control group reported a relatively high autonomous motivation for their schoolwork at baseline but did not differ significantly (see Table 2). Between Time 1 and Time 2, the autonomous motivation of the students in the intervention group as well as in the control group was maintained. The analysis showed a significant decrease of students’ autonomous motivation at Time 3 in both the intervention group and the control group. The results indicated that students’ perceived autonomous motivation decreased over time in both groups, but no significant differences were detected between the groups.

For students’ controlled motivation, there were no significant differences between the intervention group and the control group at baseline. Between Time 1 and Time 2, the controlled motivation in the intervention group as well as in the control group was maintained (see Table 2). At Time 3, both the intervention group and the control group reported maintained perceived controlled motivation. The analysis did not show any significant differences in the students’ perceived controlled motivation over time, and there were no significant differences between the groups.

6. Discussion

The aim of the present study was to test whether a teacher-focused intervention based on MI and the principles for autonomy-supportive teaching could increase teachers’ autonomy-supportive behaviors and teacher efficacy, increase students’ autonomous academic motivation and their perceptions of autonomy support, and decrease their controlled academic motivation. Our findings, using paired samples t-test, show a significant increase in teachers’ (n = 14) perceived autonomy-supportive behavior, especially when it comes to conveying confidence in their students’ abilities, which indicates that an MI-based intervention may help teachers become more autonomy-supportive. The most novel result of this study is the identification of an increase in perceived teacher efficacy, which emerged as a resource that teachers acquired during the intervention. Teacher efficacy is an important dimension of instructional quality, and this study shows that MI training can strengthen teachers’ sense of efficacy in several ways: efficacy in student engagement, efficacy in instructional strategies and efficacy in classroom management. The teachers especially reported a significant increase in teacher efficacy related to helping students to value learning, engaging students who show low interest in school, adjusting lessons to the proper level for individual students and controlling disruptive behavior in the classroom. These results can also be linked to what the teachers learned about the recommended autonomy-supportive behaviors, which previous research has shown can promote student engagement and school motivation (Reeve, 2009; Reeve & Cheon, 2021). Combining knowledge of MI skills with knowledge about these instructional behaviors may have facilitated the teachers’ application of a new teaching style that is more autonomy-supportive and student engaging. This may, in turn, have increased the teachers’ sense of efficacy.

Regarding the students’ perceptions of their teachers’ autonomy-supportive teaching style and the students’ academic motivation, there was no significant difference between the intervention group and control group from Time 1 to Time 3. There may be several reasons for this. One of the reasons might be that students in both groups (n = 478) at baseline (Time 1) rated themselves relatively highly on autonomous motivation for their schoolwork and highly rated their teacher as autonomy-supportive, thus leaving only small room for improvement and making it difficult to determine a noticeable effect (using repeated-measures ANCOVA’s). However, autonomous motivation decreased from fall to spring in both groups, which confirms previous studies showing that autonomous motivation tends to decrease within a school year (Cohen et al., 2022; Corpus et al., 2009; Opdenakker et al., 2012). The young age of the students in the current study may have limited the effect of the MI intervention. During their earliest school years, students’ desire to learn is usually very strong, but previous studies have shown that students’ motivation and commitment to academic learning decrease as they grow older (Lepper et al., 2005; Wang & Eccles, 2012). There might have been more evident differences in students’ academic motivation and perceived autonomy support if the students had been older, as students’ perceptions of autonomy support may change over time, with students getting older and thus becoming more able to differentiate between aspects of instructional quality (Wagner et al., 2016). In the Swedish school system, students in grades 5–6 (10–12 years) often have the same teacher for most subjects, which also makes it more difficult for students to compare different teachers’ teaching styles, as they do not meet many different teachers. In their meta-analysis, Tao et al. (2022) found that the relation between students’ perceived teacher support and achievement is related to grade level. Teacher support had a stronger impact on upper-secondary students than on lower-upper and elementary students (Tao et al., 2022), which was also found in a previous meta-analysis by Roorda et al. (2011), who determined that secondary students were more sensitive to teacher support and caring teacher-student relationships. Furthermore, Strait et al. (2012) suggested that given the cognitive and neurodevelopmental requirements for the MI process, there may be limitations in applying MI to younger children. Another potential reason why the results for the students’ academic motivation were non-significant is the fact that much more emphasis was focused on teaching teachers how to use MI than how to apply the SDT-based autonomy-supportive behaviors. Therefore, we suggest that future studies should focus more on the autonomy-supportive component when teachers working with students in younger ages, as previous studies of autonomy-supportive intervention programs have shown significant effects on students’ autonomous motivation (e.g., Cheon & Reeve, 2013; Cheon et al., 2019). In addition, Ahmadi et al. (in press) have built a classification system for teachers’ motivational behaviors based on SDT, which could facilitate the implementation of autonomy-supportive interventions in schools, where this classification can specify which SDT-based components were involved in effective interventions.

The students’ academic motivation did not increase in the way we had expected, but it is important to disseminate this kind of information as well and not only present significant results from MI interventions when there are also non-significant results (Strait et al., 2019). There may be many different causes for students’ decrease in autonomous motivation, but one contributing factor may be that the intervention was implemented during the COVID-19 pandemic. Due to the spread of infection, many students were absent during the intervention period, which may have affected their academic motivation as they could not go to school and meet classmates and teachers. The results may also have been affected by the extent to which the teachers had the opportunity to apply MI in their classrooms. Some of these schools also had to shift to online teaching for a few weeks when the spread of infection was very high, which also affected teachers’ ability to fully apply the relational aspects of MI.

The providers of MI in this study were the teachers themselves, who had no previous experience of MI. Miller and Rollnick (2014) argued that providers of MI should be trained to a specified criterion and tested for proficiency before delivering MI in clinical studies. With that said, we just want to highlight that the lack of effect at the student level may not have to do with MI as a method. Rather, it may be due to the difficulty of transferring new skills into implementation of practice with fidelity. Therefore, the lack of effect at student level may be due to the teachers’ lack of MI competence and proficiency. It is likely that a contributing factor was that we did not have any form of supervision for the teachers during and after the intervention. Previous studies have shown that MI competence tends to decay unless there is systematic post-training support or supervision (Soderlund et al., 2011). Although we did not detect any significant positive effects of the MI intervention on the student level, we can still see that MI has influenced teachers’ perceptions of their autonomy support and teacher efficacy. Previous research has shown that teacher efficacy influences teachers’ commitment and instructional quality (Skaalvik & Skaalvik, 2007; Tschannen-Moran & Hoy, 2001), and our study shows that MI training can contribute to supporting and strengthening the commitment of teachers, as motivated teachers are an important prerequisite for students’ learning. This study provides novel insights into the benefits of MI training for teachers, which are valuable information for teacher education and school leaders.

6.1. Limitations and suggestions for further research

The current study has limitations that need to be considered. A major limitation was that we did not have a control group with teachers that we could compare with the intervention group at both Time 1 and Time 2. Moreover, the number of participating teachers (n = 14) might be considered low. The results may also have been affected by the fact that the intervention group consisted solely of women, which may limit the generalizability of the findings to male or non-binary teachers. Hence, the teacher results should be interpreted with caution and should be replicated in larger samples. The fact that we only used two measurement points for teacher data is another limitation of the study. Without multiple follow-ups, we could not measure any possible long-term effects of the intervention. As a result, it remains unclear whether teacher outcomes were sustained over time. We, therefore, recommend future longitudinal studies to use at least three measurement points for both teacher and student data. Another limitation was that the teachers in the current study were not rated for MI proficiency, for example, with a tool such as the Motivational Interviewing Treatment Integrity (MITI), which is a widely used system for coding MI providers’ practices (Miller & Rollnick, 2014). Moreover, our study did not include observations of actual teacher-student interactions; the fidelity of the implementation is therefore uncertain. The findings are based on self-rated data, which could also be seen as a limitation. Another limitation of the study is that teacher attendance at the intervention workshops varied. Although extra workshops were offered digitally for those who were absent, not all teachers had the opportunity to participate in these workshops. Therefore, the knowledge and skills gained by the teachers in the study may not have been consistent, as those who were absent may not have gained the same skills as those who attended all five workshops. We are also aware of the fact that the teachers who participated in the study were teachers who themselves were interested in developing their relational approach and who were willing to spend both time and commitment on attending the MI training. This may have affected the outcome of the study at the teacher level, since these teachers were probably already adept at building relationships with their students, and hence rated their perception of autonomy support in the classroom on a high level even before the intervention.

Classroom interventions are challenging to implement with high fidelity, as there is much that can affect the outcome. At all measurement periods with the students, their teacher was present in the classroom. This may have affected the results, as several questions focused on the students’ perceptions of autonomy support in the classroom. The students may not have dared to answer truthfully if the teacher in question was standing next to them, which may have made them value teachers’ autonomy-supportive approach higher than if the teacher had not been present in the room. From a reliability point of view, the optimal solution would have been for the teacher not to be present. On the other hand, the class could easily become noisy and anxious if the teacher had not been present. For all students to feel comfortable, the teacher had to be present when the survey was conducted.

In future studies, it would be valuable to replicate this study with a larger sample of teachers over a longer period of time, as this intervention may have been too short to identify noticeable effects at the student level. In this current study, only teachers who voluntarily committed time and effort to learning MI participated. Therefore, it would be worthwhile to explore the experiences of teachers who participate in an MI-based intervention as part of mandatory professional development activities. It would also be interesting to investigate how much influence teachers’ own interest in professional development has on the effect of implementing MI in school by measuring their motivation and perceived competence to participate in an MI-based teacher-focused intervention before it is implemented. Further, as Tilga et al. (2021) suggest, it would be worth considering combining web-based and face-to-face approaches when designing school-based intervention programs in the future. Moreover, further research is needed to examine the effectiveness of MI-based interventions when working with older students who are at risk of dropping out of school.

7. Conclusions

The present study’s findings indicate that a brief MI-based intervention can help teachers to become more autonomy-supportive towards their students and increase teacher efficacy. Therefore, we suggest that MI training is valuable in developing teachers’ instructional styles and teaching quality. The findings also show that MI training can increase teachers’ perceived efficacy in student engagement, instructional strategies, and classroom management. However, the MI-based intervention did not increase these students’ academic motivation or perceptions of autonomy support in the classroom over time. Since the students in this study rated their academic motivation and autonomy support relatively high even before the intervention, these results suggest that school-based MI is more important for teachers’ professional development than for younger student’s academic motivation. This study demonstrates that MI training can have an impact on teachers’ instructional behaviors and increase teacher efficacy, providing valuable insights for teacher education and school leaders.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Martina S. Jordan

Martina S. Jordan is a PhD student at the Department of Educational Studies, at Karlstad University in Sweden. Her research interests include application of motivational interviewing in educational settings, student motivation, and professional development. In addition, Martina is working with motivational interviewing within sports.

Stefan Wagnsson

Stefan Wagnsson, PhD, is an associate Professor in Sport Science at Karlstad University. His research focuses on motivational processes, parental involvement and positive youth development within the context of children and youth sports. In addition to this, he is involved in coaching both individuals and teams that operate in organized sports.

Henrik Gustafsson

Henrik Gustafsson, PhD, is Professor at Karlstad University, Sweden and visiting professor at the Norwegian School of Sport Science. His research is mainly in sport psychology including the application Cognitive Behavioral Therapy in sport settings. In addition to his academic work, Henrik is also working as sport psychology consultant with athletes and coaches applying motivational interviewing in practice.