Mapping the Integration of Theory of Planned Behavior and Self-Determination Theory in Education: A Scoping Review on Teachers’ Behavioral Intentions

Abstract

Teachers’ motivation and behavioral intentions are pivotal to implementing educational innovations effectively. Understanding these processes requires theoretical frameworks that capture both deliberate decision-making and underlying motivational forces. The Theory of Planned Behavior (TPB) and Self-Determination Theory (SDT) have each contributed valuable insights, yet both face limitations when used independently. Integrating TPB and SDT may provide a more comprehensive account of how self-determined motivation shapes attitudes, subjective norms, and perceived behavioral control—the proximal predictors of intention proposed by TPB. This scoping review, conducted following the PRISMA-ScR framework, examines how TPB–SDT integration has been applied to study teachers’ behavioral intentions. A search across five databases—EBSCO, Scopus, Web of Science, ERIC, and CNKI—identified 1384 records, of which nine studies met the inclusion criteria. Most studies employed quantitative approaches, particularly structural equation modeling, while longitudinal, mixed-methods, and intervention-based designs were rare. Cross-cultural comparisons were lacking, and in-service teachers were studied more often than pre-service teachers. Findings reveal a limited but expanding body of research on TPB-SDT integration in education, with attitudes and autonomy emerging as the most consistent predictors of teachers’ intentions. This review highlights theoretical potential, methodological gaps, and directions for advancing research on teacher motivation.

1. Introduction

1.1. Teachers’ Behavioral Intentions and Theoretical Frameworks

Teachers’ behavioral intentions play a pivotal role in shaping educational practices and influencing teaching strategies, professional development, and career-related decisions (Ajzen, 1991; Klassen & Tze, 2014; Han et al., 2016). Understanding the cognitive and motivational factors that drive teachers’ intentions is essential for designing effective interventions and policies that promote positive educational outcomes (Dierendonck et al., 2024; Suárez-Mesa & Gómez, 2024).

Among the various psychological theories used to examine human behavior and the intentions to engage in specific actions within educational contexts, the Theory of Planned Behavior (TPB) (Ajzen, 1991) and the Self-Determination Theory (SDT) (Deci & Ryan, 1985; Ryan & Deci, 2000) are two of the most widely applied frameworks for explaining teachers’ motivation and decision-making (Opoku et al., 2021; Slemp et al., 2024; Wang et al., 2024; Yu et al., 2025).

While TPB emphasizes the rational, belief-based mechanisms underlying behavioral intentions, SDT focuses on the motivational processes and basic psychological needs that determine the quality of engagement. Yet, despite their complementary potential, empirical research combining these two perspectives in educational settings remain scarce and conceptually fragmented.

New findings increasingly underscore the need to bridge these perspectives, as social-cognitive predictors alone cannot fully capture the motivational processes that sustain teachers’ engagement, innovation, and adaptability in evolving educational contexts (Cheon et al., 2022; Ocete et al., 2025).

1.2. Theory of Planned Behavior (TPB)

The TPB posits that behavior is primarily determined by behavioral intention, which is shaped by three main factors: attitude toward the behavior, subjective norms, and perceived behavioral control (Ajzen, 1991). Attitude reflects personal evaluations; subjective norms refer to perceived social expectations; and perceived behavioral control (PBC) denotes an individual’s sense of capability to perform the behavior (Armitage & Conner, 2001; Steinmetz et al., 2016). In educational contexts, these constructs have been widely applied to understand teachers’ engagement in innovative practices, use of technology, and professional development (Han & Yin, 2016).

TPB provides a well-structured framework for understanding how beliefs are translated into intentions and actions in educational settings (Armitage & Conner, 2001; Steinmetz et al., 2016). Nevertheless, while TPB has been widely applied in the study of teacher behavior, its focus on social-cognitive determinants means that it does not address the nature or quality of the motivation underlying these intentions. This limitation highlights the importance of integrating TPB with complementary theoretical perspectives such as SDT.

Recent studies have shown that behavioral intention alone does not fully account for teachers’ sustained engagement or adoption of innovative practices, which often depend on autonomous motivation and deeply internalized values (Han & Yin, 2016; Menéndez-Espina et al., 2025). This limitation indicates that cognitive models such as TPB should be complemented by motivational perspectives like SDT, which provide deeper insight into the quality and persistence of behavioral enactment.

1.3. Self-Determination Theory (SDT)

In contrast, SDT provides a motivational lens that explains behavior in terms of the satisfaction of three basic psychological needs—autonomy, competence, and relatedness—which foster autonomous motivation and self-regulated behavior (Deci & Ryan, 1985; Ryan & Deci, 2000, 2017). As described by Ateş and Yilmaz (2024), autonomy involves self-regulation and volitional control over one’s actions, competence refers to the sense of mastery and effectiveness in task performance, and relatedness concerns the need to establish meaningful social connections and belonging. In teaching, these needs are linked to instructional freedom, perceived professional efficacy, and social connectedness within the school community (Gorozidis & Papaioannou, 2014). SDT distinguishes between autonomous and controlled forms of motivation, a distinction that has proven critical in explaining teachers’ engagement and persistence (Wang et al., 2024; White et al., 2021).

When these needs are satisfied, individuals are more likely to act with volition and experience intrinsic motivation, whereas frustration of these needs leads to controlled or externally regulated behavior (Deci & Ryan, 1985; Ryan & Deci, 2000, 2017). The theory thus emphasizes not only the amount but also the quality of motivation, situating behavior along a continuum from externally regulated to fully self-determined forms of motivation (Ryan & Deci, 2000, 2017).

This framework has been increasingly applied to investigate teacher motivation and professional development across diverse educational settings (Gorozidis & Papaioannou, 2014; Suárez-Mesa & Gómez, 2024; Wang et al., 2024). Nevertheless, while SDT provides valuable insights into the sources and quality of motivation, it does not explicitly explain how motivational orientations translate into behavioral intentions and actions (Hagger & Chatzisarantis, 2009). Conversely, TPB specifies the socio-cognitive mechanisms underlying intention formation. Understanding how these two frameworks complement each other provides the conceptual basis for the integrative perspective discussed in Section 1.4.

1.4. Toward an Integrated Framework

An emerging perspective in health, sport, and educational psychology is that integrating SDT and TPB can address the theoretical limitations of each model (Hagger & Chatzisarantis, 2009; Ntoumanis, 2001; Wilson & Rodgers, 2004; Al-Jubari, 2019). SDT explains the origins of motivation, while TPB outlines the proximal cognitive mechanisms—attitudes, subjective norms, and PBC—that predict intentions. For instance, some authors propose a motivational sequence in which self-determined motivation (SDT) functions as a distal predictor of TPB components, which in turn serve as proximal predictors of behavioral intentions and actions (Hagger et al., 2006; Brooks et al., 2017). In this way, SDT provides an account of the internalization processes that underlie the belief system central to TPB, clarifying whether attitudes and control perceptions arise from autonomous or controlled motives (Luqman et al., 2017).

Empirical research in health-related domains (e.g., exercise, diet, and physical education) has consistently supported this integrative approach, showing that self-determined motivation enhances attitudes and perceived control, thereby increasing behavioral intentions (Chung et al., 2017; Brooks et al., 2017). Despite these advances, educational research has been slow to adopt such integration, even though teaching is an inherently self-regulated, value-laden, and socially influenced activity. A few recent studies—such as those examining teachers’ technology adoption (Ateş & Yilmaz, 2024) and professional engagement (Gorozidis & Papaioannou, 2014)—have begun to operationalize TPB–SDT models, yet findings remain scattered, methodologically narrow, and conceptually inconsistent. No comprehensive synthesis has yet mapped how this integration has been implemented, what constructs are emphasized, and where theoretical or methodological gaps persist.

Thus, the current review addresses a clear gap: although TPB–SDT integration has shown strong predictive validity in other behavioral domains, its potential for explaining teachers’ motivational and intentional processes remains underexplored and undertheorized. An overview is therefore warranted to consolidate existing evidence and guide future research toward a unified model of teacher motivation that bridges cognitive and motivational determinants.

Although TPB provides a solid structure for examining how social-cognitive factors influence intention and behavior, it has been criticized for failing to capture the role of intrinsic motivation and basic psychological needs (Sniehotta et al., 2013; Hagger & Chatzisarantis, 2009). SDT addresses this limitation by focusing on internal motivational processes, explaining how the satisfaction of autonomy, competence, and relatedness shapes the quality of motivation along a continuum from controlled to autonomous forms (Ryan & Deci, 2000, 2017).

Recent studies have advocated for the integration of TPB and SDT to capture both external influences and internal motivational dynamics, thereby providing a more comprehensive framework to explain teachers’ behavioral intentions (Ateş & Gündüzalp, 2024; Gorozidis & Papaioannou, 2014; Wijaya et al., 2024). However, evidence from health and related domains indicates that most integrative studies continue to rely primarily on cross-sectional and quantitative designs, with limited longitudinal validation (Hagger & Chatzisarantis, 2009). Although a few recent intervention-based attempts have emerged (e.g., Caso et al., 2024), such studies remain the exception rather than the norm. By contrast, within the educational field, research explicitly combining TPB and SDT is still scarce, underscoring the need for deeper theoretical and methodological investigation.

Figure 1 illustrates this integrative framework: motivational constructs from SDT (autonomy, competence, relatedness) influence motivation, which—together with TPB constructs (attitude, subjective norm, and perceived behavioral control)—predict behavioral intention. As noted earlier, this integration is valuable because SDT offers a lens for understanding motivational processes, while TPB clarifies socio-cognitive pathways to intention. Together, they provide a more comprehensive explanation of teachers’ behavioral intentions in educational settings.

While several reviews and meta-analyses have examined TPB or SDT independently within educational contexts (Erten & Köseoğlu, 2022; Howard et al., 2021; Wang et al., 2024), only a limited number of studies have investigated their joint application, particularly in teacher-related research. Given the crucial role of motivational and behavioral theories in education, a comprehensive understanding of their integrated use and theoretical interplay is essential. Accordingly, this underscores the need for a scoping review to map existing research, identify dominant theoretical and methodological approaches, and pinpoint key research gaps in the field.

1.5. Aim of This Study and Research Objectives

The aim of this scoping review is to examine how TPB and SDT have been integrated to explain teachers’ behavioral intentions across educational contexts. Specifically, this review seeks to (a) map the theoretical rationales and integration strategies used in prior studies, (b) identify methodological tendencies and limitations, and (c) highlight conceptual and empirical gaps for future research.

By synthesizing existing evidence, this study contributes to both theory and practice; theoretically, it clarifies how integrating TPB and SDT can advance understanding of the interplay between motivation and cognition in teaching, and practically, it informs the design of interventions aimed at fostering autonomous, intentional, and sustained professional behavior among teachers.

Accordingly, the review is guided by the following research questions (RQ):

RQ1.

In what ways have TPB and SDT been integrated in educational research to explain teachers’ behavioral intentions?

RQ2.

What methodological approaches and analytical strategies are most employed in studies that combine TPB and SDT?

2. Materials and Methods

2.1. Protocol and Screening Process

This scoping review was conducted following the PRISMA Extension for Scoping Reviews (PRISMA-ScR; Tricco et al., 2018), which offers a standardized framework to ensure methodological transparency and rigor in the identification, screening, and selection of relevant literature. The screening and selection process is summarized in a PRISMA-ScR flow diagram (see Figure 2), which depicts the number of records identified, screened, excluded, and included at each stage.

2.2. Eligibility Criteria

To ensure the relevance and rigor of the studies analyzed in this scoping review, we applied a set of clearly defined inclusion criteria. Eligible studies included those reporting empirical research—whether quantitative, qualitative, or mixed-method—and grounded in a clearly defined theoretical framework. In contrast, purely conceptual discussions without an empirical application of either TPB or SDT were excluded. For instance, theoretical papers outlining the general principles of SDT without empirical testing them were not retained, whereas studies that operationalized TPB and SDT constructs through surveys or interviews with teachers were considered eligible.

A central requirement for inclusion was the integration of TPB and SDT in examining teachers’ behavioral intentions. Studies combining TPB and SDT with an additional theoretical perspective—such as Social Cognitive Theory or the Technology Acceptance Model—were considered, provided that TPB and SDT remained the primary components of the theoretical framework. For example, two included studies incorporated the Technology Acceptance Model (TAM) alongside TPB and SDT to explain teachers’ adoption of digital tools but were retained because TPB and SDT served as the main explanatory basis. Furthermore, research primarily based on another framework but explicitly incorporating TPB and SDT constructs in its analysis was included when it offered a substantive methodological or theoretical contribution.

The target population of the selected studies included pre-service teachers, in-service teachers, and individuals formally engaged in teaching roles, such as teacher educators or adjunct faculty. With respect to publication type, only journal articles and full-text conference papers were considered, with peer-reviewed sources prioritized. Non-peer-reviewed publications were not automatically excluded if they provided relevant empirical insights; for example, one conference proceeding without formal peer review was retained because it reported original data based on TPB and SDT constructs. In contrast, unpublished manuscripts and dissertations were excluded to ensure consistency with the standards of major academic databases.

To capture both recent developments and earlier contributions to the integration of TPB and SDT in educational research, the review focused on studies published between 2010 and 2024. This 15-year window was considered appropriate as it balances the inclusion of foundational studies with contemporary research, following methodological guidance for scoping reviews that recommend aligning the time frame with the maturity of the field and the balance between comprehensiveness and manageability (Peters et al., 2020; Gottlieb et al., 2021; Mak & Thomas, 2022).

Finally, studies written in English, Spanish, or Chinese were included. English was selected as it represents the dominant language of international academic publishing. Spanish and Chinese were included to broaden the geographical and cultural coverage of the review, capturing relevant research conducted in two of the largest educational systems worldwide. This multilingual approach enhances the diversity and representativeness of the evidence base.

2.3. Search Strategy

Based on the predefined inclusion and exclusion criteria, a structured search strategy was designed to identify relevant studies across multiple academic databases. This section provides a detailed account of the search process, including the selected databases, keywords strategies, and filtering techniques.

2.3.1. Database Selection

To ensure comprehensive and interdisciplinary exploration of research integrating TPB and SDT in education, the search encompassed several key sources—namely, Scopus, Web of Science (WoS), EBSCO, ERIC, and CNKI—each selected for a specific purpose as detailed below:

• Scopus and WoS: For their robust bibliometric data and coverage of high-impact interdisciplinary journals.
• EBSCO (specifically, the “Academic Search Complete” and “Education Research Complete” subcollections): To access an extensive repository of education-focused studies, including those not indexed in larger multidisciplinary databases.
• ERIC (Education Resources Information Center): For its exclusive focus on educational research, ensuring a strong emphasis on studies related to teachers’ behavioral intentions.
• CNKI (China National Knowledge Infrastructure 中国知网): To incorporate Chinese-language literature, expanding the cultural and linguistic diversity of the review. Searches were conducted via the international version of CNKI (https://oversea.cnki.net/ (accessed on 26 September 2025)). Full texts were accessed through institutional partnerships or by direct contacting authors when access was restricted.

2.3.2. Search Strategy and Filtering Techniques

The search strategy was adapted for each of the above-mentioned databases (see Section 2.3.1) to accommodate platform-specific functionalities and constraints. Boolean operators were consistently applied to maximize coverage and ensure the retrieval of studies integrating the TPB and SDT.

Table 1. Provides a summary of the search fields, Boolean combinations, and temporal filters applied across the selected databases.

Database	Search Field	Boolean Combination	Temporal Filter
EBSCO	Title, Abstract, Keywords	(“Theory of Planned Behavior” OR “TPB”) AND (“Self-Determination Theory” OR “SDT”)	2010–2024 (due to export restriction)
ERIC	Title, Abstract, Keywords	(“Theory of Planned Behavior” OR “TPB”) AND (“Self-Determination Theory” OR “SDT”)	No filter applied
Scopus	TITLE-ABS-KEY fields	(“Theory of Planned Behavior” OR “TPB”) AND (“Self-Determination Theory” OR “SDT”)	No filter applied
WoS	Topic (Title, Abstract, Keywords)	(“Theory of Planned Behavior” OR “TPB”) AND (“Self-Determination Theory” OR “SDT”)	No filter applied
CNKI	Title, Abstract, Keywords (in Chinese) *	(“计划行为理论”) AND (“自我决定理论”)	No filter applied

* Note: CNKI keywords translated as: “Theory of Planned Behavior” = “计划行为理论”; “Self-Determination Theory” = “自我决定理论”.

summarizes the search fields, Boolean combinations, and temporal filters used across the five selected databases.

These databases typically index non-English publications with English abstracts and keywords, this review primarily employed English search terms (“Theory of Planned Behavior” OR “TPB”) AND (“Self-Determination Theory” OR “SDT”). For CNKI, the equivalent Chinese terms (“计划行为理论” AND “自我决定理论”) were applied. This strategy was expected to capture most relevant studies in Spanish and Chinese. However, some studies may have been missed if their abstracts did not include the corresponding English terms, representing a potential limitation. Nonetheless, this limitation is likely minimal due to the standard indexing practices of major databases.

Because the combination of “TPB” and “SDT” already generated a manageable number of results, no additional search terms such as “teacher*” were included; teacher-related studies were identified during the screening process. Although truncation and wildcards (e.g., teach* to capture teacher, teachers, or teaching) are commonly used to expand search coverage, the present review relied exclusively on exact terms. While this approach may have excluded certain lexical variations, such as plural forms or British/American spelling differences (e.g., behaviour vs. behavior), the specificity of the combined terms “TPB” and “SDT” makes the likelihood of omitting relevant studies minimal.

A total of 1384 records were identified from the five selected databases. After removing 246 duplicates and one retracted paper, 1137 unique records remained for title and abstract screening. During this phase, 1126 records were excluded as they were not related to TPB and SDT integration. Following a full-text review of the 11 selected studies, 9 were ultimately included in the final analysis. Two studies, despite containing key constructs from both TPB and SDT, did not explicitly integrate the two theories and were therefore excluded. The step-by-step selection process is illustrated in the PRISMA-ScR flow diagram shown in Figure 2.

2.4. Data Extraction and Synthesis

Data from each included study were extracted into a standardized matrix capturing country, sample type, research design, integration mode, SDT constructs, TPB constructs, and significant pathways. For the synthesis, we focused exclusively on the core constructs of TPB (attitude, subjective norm, perceived behavioral control, intention) and SDT (autonomy, competence, relatedness, motivation). When additional models (e.g., TAM) were included, their constructs were documented descriptively but excluded from cross-study frequency counts to ensure comparability across studies. All data were organized and analyzed using structured Excel tables.

3. Results

3.1. Overview of Included Studies

After applying the inclusion and exclusion criteria, a total of nine studies were identified and included in this scoping review (

Table 2. Summary of the studies included.

ID	Authors (Year)	Title	Journal	Country	Sample	Research Type	Constructs Analyzed
1	Ateş and Gündüzalp (2024).	A unified framework for understanding teachers’ adoption of robotics in STEM education	Education and Information Technologies	Turkey	In-service teachers	quantitative	Autonomy, competence, relatedness, attitude, subjective norms, perceived behavior control, and intention
2	Ateş and Yilmaz (2024)	A comprehensive model explaining teachers’ intentions to use mobile-based assessment	Interactive Learning Environments	Turkey	In-service teachers and pre-service teachers	quantitative	Autonomy, competence, relatedness, attitude, subjective norms, perceived behavior control, and intention
3	Chasteen and Chattergoon (2020)	Insights from the Physics and Astronomy New Faculty Workshop: How Do New Physics Faculty Teach?	Physical Review Physics Education Research	USA	In-service teachers	quantitative	Relatedness, competence, autonomy, attitude, subjective norms, and perceived behavior control
4	Cui et al. (2022).	Understanding K12 Teachers’ Continuance Intention and Behavior toward Online Learning Communities	Conference paper	China	In-service teachers	quantitative	Autonomy, competence, relatedness, attitude, subjective norms, perceived behavior control, intention-continuance, intention, and behavior
5	Cullen and Greene (2011)	Preservice Teachers’ Beliefs, Attitudes, and Motivation about Technology Integration.	Journal of Educational Computing Research	USA	Pre-service teachers	qualitative	Intrinsic motivation, extrinsic motivation, amotivation, subjective norms, perceived behavior control, and intention
6	Hur et al. (2024)	Why Pursue a Career in Teaching Agriculture? Application of Self-Determination Theory and the Theory of Planned Behavior	Journal of Agricultural Education	USA	Pre-service teachers	Mixed approach	Intrinsic motivation, identified regulation, introjected regulation, external regulation, amotivation, attitude, subjective norms, perceived behavior control, intention, and behavior
7	Kupers et al. (2024).	Explaining teachers’ behavioral intentions towards differentiated instruction for inclusion: Using the theory of planned behavior and the self-determination theory.	European Journal of Special Needs Education	The Netherlands	In-service teachers	quantitative	Perceived autonomy, perceived competence, perceived relatedness, attitudes, perceived behavior control, subjective norms, and behavioral intentions
8	Ren (2024).	Modeling college EFL teachers’ intentions to conduct academic research: Integrating theory of planned behavior with self-determination theory.	PLoS ONE	China	In-service teachers	quantitative	Autonomous motivation, Controlled motivation, Attitudes, Subjective norms, Perceived Behavior Control
9	Wijaya et al. (2024)	Critical factors affecting the participation of mathematics teachers in professional development training	Current Psychology	China	In-service teachers	quantitative	Relatedness, participating interest, training value, facilitating conditions, quality of training, attitude, subjective norms, training optimism (treated as a TPB-related belief/expectancy variable in this model), and participation intention (as the TPB dependent variable)

). The initial database search yielded 1137 studies, which were screened in multiple stages. Most were excluded due to their limited scope or lack of theoretical integration, resulting in nine final studies that explicitly integrate both TPB and SDT in teacher-related educational research.

The included studies were conducted in Turkey, China, the Netherlands and the United States of America (USA), with sample sizes ranging from 31 to 605 participants. They involved pre-service teachers, in-service teachers, or both, across diverse professional contexts, although the primary focus was on teaching practice and professional development.

Regarding research design, the majority (8 out of 9) employed quantitative methods, typically using cross-sectional surveys analyzed through structural equation modeling (SEM). Only one study adopted a qualitative approach, and just one study used a longitudinal design, providing insights into the temporal dynamics of motivational and cognitive processes.

Overall, these nine studies illustrate both the potential and current constraints of TPB–SDT integration in teacher-focused research. While they offer valuable insights into teachers’ motivation and behavioral intentions, the limited number of studies, methodological concentration, and narrow contextual focus underscore the need for further exploration. Most studies applied the integration of TPB and SDT to examine teachers’ motivation and intention to adopt innovative or student-centered teaching practices (n = 6). Quantitative, cross-sectional designs predominate, while longitudinal (n = 1) and cross-cultural perspectives (n = 0) remain rare. These patterns indicate that research on TPB–SDT integration in education is still at an early stage, with substantial opportunities for theoretical and methodological advancement.

3.2. TPB and SDT Integration in Educational Research in Response to RQ1

3.2.1. Theoretical Integration Approaches

Across the nine studies, three recurrent integration logics were identified: parallel, sequential, and mixed approaches. This typology was inductively derived from the included studies. Similar distinctions have been noted in prior discussions of theory integration, differentiating between additive/independent and mediated/sequential models, as well as more selective or partial approaches (Hagger & Chatzisarantis, 2009, 2016; Jaccard & Blanton, 2005; Whetten, 1989).

Parallel models treat SDT and TPB variables as independent predictors of intentions or behaviors. For instance, Kupers et al. (2024) examined teachers’ intentions toward differentiated instruction by comparing TPB predictors (attitudes, subjective norms, and perceived behavioral control) and SDT needs (autonomy, competence, and relatedness) as separate explanatory pathways, showing that attitude and autonomy were the strongest predictors. Similarly, Chasteen and Chattergoon (2020) mapped constructs such as self-efficacy onto both TPB and SDT dimensions to explain the adoption of active learning, while Hur et al. (2024) explored qualitatively how SDT motivations and TPB beliefs coexisted in shaping teachers’ career intentions. Overall, parallel integration highlights the independent and complementary contributions of SDT and TPB without assuming directional links between them.

Sequential models specify SDT constructs as antecedents of TPB predictors, which subsequently shape intentions. Ren (2024), for example, demonstrated how autonomous and controlled motivation predicted attitudes, subjective norms, and perceived control, which in turn predicted research intentions among EFL teachers. Likewise, Ateş and Yilmaz (2024) in Turkey showed that autonomy, competence, and relatedness influenced perceived usefulness and ease of use, which shaped attitudes and ultimately intentions, with subjective norms and perceived behavioral control exerting additional direct effects. This sequential logic illustrates how SDT variables can serve as motivational foundations that channel through TPB predictors to explain intentions.

Mixed integration involves the selective use of SDT constructs or the introduction of context-specific adaptations alongside TPB variables, rather than applying the full SDT framework. In China, Wijaya et al. (2024) combined a single SDT need (relatedness) with several training-related factors (participating interest, training value, and quality of training), as well as facilitating conditions from technology adoption research (Venkatesh et al., 2003), to predict participation intention and subsequent TPB-based outcomes. Cui et al. (2022) presented another form of mixed integration, in which SDT needs predicted satisfaction, which in turn influenced intentions and behaviors, while TPB predictors operated in parallel. This illustrates a selective adaptation by inserting an intermediate construct rather than linking SDT needs directly to TPB predictors. Finally, Cullen and Greene (2011) modeled SDT motivation types (intrinsic, extrinsic, and amotivation) as outcomes predicted by TPB variables, producing a non-symmetric configuration that only partially reflects SDT’s theoretical structure. Collectively, these studies exemplify how mixed integrations adapt or truncate SDT constructs when combined with TPB, resulting in less systematic but contextually responsive models.

3.2.2. Constructs from SDT and TPB

Among the included studies, five of them examined SDT constructs were the three basic psychological needs—autonomy, competence, and relatedness. These needs were repeatedly incorporated in sequential or parallel models, such as in Ateş and Yilmaz (2024) and Kupers et al. (2024). In addition, several studies focused on motivation types (e.g., autonomous versus controlled motivation, or intrinsic, extrinsic, and amotivation), particularly in Ren (2024), Cullen and Greene (2011), and Hur et al. (2024). Together, these SDT constructs underscore the central role of motivational determinants in the integration of SDT with TPB.

Alongside these core constructs, some studies introduced context-specific or rarely used SDT-related variables. Wijaya et al. (2024), for example, included participating interest, training value, facilitating conditions, and quality of training, of which only relatedness aligns with a core SDT need. Cui et al. (2022) employed satisfaction as a mediator bridging SDT needs to TPB pathways, thereby adapting the framework to the context of online learning communities. These adaptations reflect the flexibility of SDT but also indicate that not all variables correspond directly to foundational psychological needs.

The TPB side of the integration was more consistent. Nearly all studies relied on the three core predictors—attitudes, subjective norms, and perceived behavioral control (PBC)—together with behavioral intentions, while a few studies extended their models to include actual behavior, serving as the ultimate outcome of the TPB framework, most notably Cui et al. (2022) and Kupers et al. (2024). In addition, some studies extended the TPB model with context-specific beliefs, such as training optimism (a construct introduced by Wijaya et al., 2024) or perceived usefulness and ease of use drawn from the Technology Acceptance Model (Ateş & Gündüzalp, 2024).

Overall, the findings indicate that TPB and SDT are most frequently integrated in studies examining teachers’ motivation and intentions to adopt innovative practices, whereas longitudinal and cross-cultural investigations remain rare.

3.3. Methodological Approaches and Analytical Strategies in Response to RQ2

3.3.1. Methodological and Contextual Characteristics

In terms of research design, the included studies were predominantly quantitative, relying on cross-sectional survey data. Qualitative approaches were rare, with only one study adopting a fully qualitative design to explore teachers’ motivations (Hur et al., 2024). None of the studies employed a mixed-methods design. Longitudinal approaches were also scarce, with only one study (Chasteen & Chattergoon, 2020) examining changes in teaching practices over time.

With respect to analytical methods, SEM was the dominant tool, reflecting a methodological concentration on path modeling approaches. A few exceptions existed: Cullen and Greene (2011) employed regression analysis instead of SEM, Hur et al. (2024) applied coding procedures in a qualitative design, and Chasteen and Chattergoon (2020) relied on trend analyses in their longitudinal study.

The geographical distribution of studies shows a strong concentration in China and Turkey, which together accounted for most of the quantitative SEM-based contributions. Smaller numbers of studies originated from the USA and the Netherlands, while no research was identified from regions such as Latin America, Africa, or the Global South more broadly. This narrow distribution limits the cultural and educational contexts in which SDT–TPB integration has been empirically tested.

In terms of target populations, most studies (seven out of nine) focused on in-service teachers, often in relation to teaching practice, professional development, or technology adoption. Two studies investigated pre-service teachers (e.g., Cullen & Greene, 2011; Hur et al., 2024), and one study included both groups. Overall, pre-service teachers were less frequently represented compared to their in-service counterparts.

3.3.2. Summary of Predictive Patterns

The analysis of the nine studies revealed two recurrent patterns, according to Cohen’s correlation guidelines (Gignac & Szodorai, 2016), in how SDT and TPB constructs predict teachers’ intentions.

First, attitudes and autonomy frequently emerged as influential predictors, although their strength varied across contexts. In several studies, both constructs exerted large effects on teachers’ intentions—for instance, Kupers et al. (2024) reported strong effects for attitudes (β = 0.57) and autonomy (β = 0.57), while Ateş and Yilmaz (2024) found that attitudes predicted intentions (β = 0.49) and autonomy significantly shaped beliefs about usefulness and ease of use (β ≈ 0.23–0.25). Ren (2024) likewise showed that autonomous motivation indirectly influenced intentions by predicting attitudes, subjective norms, and perceived control. At the same time, smaller or non-significant effects were also reported, such as the weak role of attitude in Cui et al. (2022) (β = 0.16) and its non-significance in Wijaya et al. (2024), or the non-significant effect of autonomy on satisfaction in Cui et al. (2022). Taken together, these findings indicate that attitudes and autonomy often play central roles, but their predictive strength is not uniform across studies, highlighting the need for further synthesis to establish more consistent evidence.

Second, several predictors demonstrated weaker or more variable effects across studies. For instance, relatedness often showed only modest or context-dependent associations (e.g., Kupers et al., 2024; Cui et al., 2022), and subjective norms were significant in some models (Ren, 2024; Ateş & Yilmaz, 2024) but not in others (Cui et al., 2022). Similar variability was observed for other constructs such as competence, perceived behavioral control, or specific motivation types, which were not consistently strong across all studies. These findings suggest that while social connectedness and normative influences—and indeed several other determinants—can play a role in shaping teachers’ intentions, their predictive strength tends to be more context-specific and less uniform than that of attitudes or autonomy.

4. Discussion

In response to RQ1 and RQ2, this scoping review identified nine studies that explicitly integrated TPB and SDT in teacher-related research, most of which relied on quantitative, cross-sectional survey data analyzed through SEM and were concentrated in China and Turkey. Across these studies, three integration logics emerged—parallel, sequential, and mixed—reflecting different ways of linking motivational and cognitive determinants. In terms of predictive patterns, attitudes and autonomy frequently appeared as central predictors of teachers’ intentions, although their effects varied considerably across contexts. By contrast, relatedness and subjective norms generally played weaker or less consistent roles. Overall, the evidence highlights both the promise and the current limitations of combining TPB and SDT, with results suggesting the need for further synthesis and broader empirical testing.

4.1. Theoretical Implications

This review contributes to theoretical understanding in several ways.

First, the integration typology identified across the studies illustrates different logics of combining motivational and social-cognitive perspectives. In parallel models, TPB and SDT constructs operate as independent predictors, providing complementary explanatory power without positing causal links between the two theories. In sequential models, SDT constructs act as motivational antecedents that shape TPB predictors, which then channel into intentions, thereby offering a more nuanced account of how underlying needs and motivations are translated into beliefs and perceived control. Finally, mixed integrations reveal how researchers adapt the frameworks to specific contexts by including only selected SDT constructs or by inserting context-specific mediators (e.g., satisfaction). While such flexibility can enhance contextual fit, it also risks weakening the theoretical consistency of SDT.

Second, the findings offer variable-specific insights into the motivational and cognitive determinants of teacher behavior. Attitudes from TPB and autonomy from SDT consistently emerged as the strongest predictors of teachers’ intentions. This underscores the importance of both positive evaluative beliefs and a sense of volition as dual drivers of educational practice. By contrast, relatedness showed weaker and less consistent effects, suggesting that social connectedness may play a more limited role in predicting teachers’ professional behaviors—possibly reflecting the high degree of autonomy and professional responsibility characteristic of teaching.

4.2. Methodological Implications

From a methodological perspective, the evidence base is overwhelmingly quantitative, with survey-based SEM approaches dominating the field. This emphasis ensures statistical rigor and comparability across studies but limits insights into the dynamic and contextual processes underlying teachers’ motivations and beliefs. In contrast, qualitative work remains underrepresented: only Hur et al. (2024) provided an in-depth qualitative account, which demonstrated the added value of capturing lived experiences and contextual nuances that are often overlooked in survey research.

The dominance of cross-sectional quantitative designs can be partly attributed to the methodological traditions of educational psychology, where structural equation modeling (SEM) is commonly used to test theoretical integration. Researchers may favor such designs because they allow the simultaneous estimation of complex relationships among multiple constructs, which align with the multidimensional nature of TPB and SDT. Additionally, practical constraints such as limited access to longitudinal samples and institutional pressure for statistically robust findings often lead to a preference for cross-sectional survey methods.

However, this methodological concentration also has implications for the validity of TPB–SDT integration. The reliance on single-time-point data restricts causal inference and limits the ability to capture the dynamic evolution of motivational and cognitive determinants over time. Consequently, the interplay between SDT-based needs satisfaction and TPB-based belief structures may appear stable or linear due to the reliance on single-time-point data. Without longitudinal or experimental evidence, it is impossible to determine whether the relationships proposed in parallel, sequential, or mixed TPB–SDT models represent genuine causal mechanisms or merely cross-sectional associations driven by statistical convenience. Thus, while SEM-based quantitative research provides valuable statistical rigor, it tends to portray TPB–SDT interactions as more static than they might be in practice.

From a geographical perspective, most studies originated from China and Turkey, with only a few contributions from the USA and the Netherlands. This concentration may reflect national policy priorities in teacher training and professional development, as well as the popularity of SEM-based research in these academic communities. However, the lack of representation from other regions raises concerns about cultural specificity, since educational policies, institutional practices, and cultural norms may significantly shape how SDT and TPB constructs operate, with potential variation across cultural contexts. Similarly, the sample composition was skewed toward in-service teachers, while pre-service populations were much less represented. This imbalance makes it difficult to generalize findings to teacher training and early-career contexts, where motivational processes may differ substantially.

4.3. Practical Implications

The findings also yield important practical implications for teacher education and professional development. The consistent importance of autonomy and attitudes suggests that interventions aiming to strengthen teachers’ sense of volition and positive evaluations of innovative practices may be particularly effective. This has clear relevance for emerging domains such as education for sustainable development (ESD) and the integration of artificial intelligence (AI) in teaching. Professional development that fosters autonomy support and cultivates constructive attitudes can enhance both pre-service and in-service teachers’ intentions to adopt these practices in their classrooms.

To translate these insights into practice, teacher training programs should incorporate explicit components that foster autonomy-supportive teaching and reflective self-evaluation. For example, mentoring systems (Ifarajimi et al., 2025), improving teacher resiliency (Vestal et al., 2025), and collaborative learning communities (Ghimire & Singh, 2025) can be structured around choice, perspective taking, and acknowledgment of teachers’ professional agency—principles consistent with SDT. Similarly, integrating reflective tasks that help teachers analyze their own attitudes toward innovation can make TPB-based attitudinal change more intentional and sustainable. In pre-service contexts, embedding these principles into practicum design or microteaching sessions can strengthen the link between motivational experiences and behavioral intentions.

Training formats that prioritize autonomy, rather than emphasizing compliance, are therefore more likely to promote lasting improvements in areas such as inclusive education, differentiated instruction, and technology adoption. In turn, such approaches can create motivationally supportive environments that sustain teachers’ engagement beyond the short-term effects of policy mandates, aligning with the broader goal of fostering education for sustainable development.

At the policy level, the evidence suggests that mandates and normative pressures alone may be insufficient; instead, autonomy-supportive environments that strengthen teachers’ volition and positive attitudes toward new pedagogical approaches are more likely to foster lasting improvements in practice. Designing professional development policies that emphasize teachers’ self-determination—such as granting flexibility in instructional design, recognizing intrinsic motivation, and supporting peer learning—could bridge the gap between external reform efforts and teachers’ internalized intentions to innovate.

4.4. Limitations of the Review

This scoping review is subject to several limitations that should be acknowledged explicitly. First, the small number of studies included (n = 9) limits the breadth of evidence available and constrains the generalizability of the conclusions. The review therefore provides an initial mapping rather than a comprehensive synthesis of the TPB–SDT literature.

Second, the search strategy relied primarily on English, Chinese, and Spanish databases, and may have overlooked relevant work published in other languages. This linguistic limitation potentially narrows the global representativeness of the evidence base.

Third, the dominance of studies from China and Turkey, combined with the absence of research from other cultural and institutional contexts, restricts cross-cultural comparability. Consequently, the transferability of the observed integration patterns to other educational systems should be interpreted with caution.

Fourth, this review did not conduct a meta-analysis, and findings are therefore descriptive and integrative rather than statistically aggregated. As a result, the relative strength or consistency of specific TPB–SDT relationships cannot be quantitatively compared across studies.

Finally, the operationalization of constructs varied considerably across studies, particularly in relation to SDT. While some studies adhered closely to the three basic needs, others employed context-specific adaptations such as training value or facilitating conditions, which may weaken theoretical coherence and reduce the validity of comparisons across models.

Together, these methodological constraints suggest that the current evidence should be viewed as exploratory rather than confirmatory, providing a preliminary but valuable overview of how TPB and SDT have been integrated in teacher-related research.

5. Conclusions

This review identified nine studies that integrated the Theory of Planned Behavior (TPB) and Self-Determination Theory (SDT) in teacher-related research. Three main approaches emerged—parallel, sequential, and mixed—reflecting different ways of linking motivational and social-cognitive perspectives. Across studies, attitudes and autonomy consistently appeared as the strongest predictors of teachers’ intentions, whereas relatedness, competence, and subjective norms played weaker or more context-dependent roles. Methodologically, the field remains dominated by cross-sectional SEM-based surveys, with limited qualitative or longitudinal work, and geographically concentrated in China and Turkey. These patterns highlight both the promise and the limitations of TPB–SDT integration: while the combination of evaluative beliefs and psychological needs offers valuable explanatory power, future research should broaden cultural contexts, include more pre-service teachers, diversify methods, and preserve conceptual clarity by focusing on the core constructs of SDT.

Beyond summarizing these findings, this review contributes to the literature by mapping how TPB and SDT have been jointly applied in teacher-related studies, identifying conceptual patterns and methodological tendencies that have not been previously synthesized. By highlighting the main routes through which motivational and cognitive determinants interact, the review offers a clearer conceptual basis for future research designs and theoretical integration.

Furthermore, the findings of this review underscore the potential for expanding such integration. For instance, studies like Ateş and Gündüzalp (2024) demonstrate that combining TPB and SDT with complementary frameworks such as the Technology Acceptance Model (TAM) can provide deeper explanatory insights into teachers’ technology adoption and motivational processes. These developments reinforce the conceptual value of integrating multiple theoretical perspectives to capture the complex determinants of teacher behavior—an approach that this review systematically extends to the domain of educational motivation.

From a practical standpoint, the insights gained here can inform teacher education and professional development programs aimed at enhancing motivation and behavioral intention, particularly by fostering autonomy-supportive environments and strengthening positive attitudes toward innovative teaching. Future studies should explore how the integration of TPB and SDT can inform interventions that promote teachers’ long-term motivation and adaptive teaching behaviors across diverse educational contexts.