Mathematics is a fundamental discipline that determines individuals’ success in their academic and professional lives, spanning a wide range from abstract thinking to solving everyday problems. However, this discipline is also at the center of intense anxiety, lack of self-confidence, and negative attitudes for many students worldwide. While traditional mathematics education has focused primarily on cognitive skills and pedagogical methods, research over the past half-century has demonstrated that affective and psychological factors are at least as decisive as cognitive skills (Dowker et al., 2016). Students’ attitudes toward mathematics, their anxieties, motivations, self-efficacy beliefs, and tolerance not only shape their participation in learning processes but also influence their long-term academic success and even their career choices (Jansen and Middleton, 2011; Hannula, 2012).

Within this framework, a growing body of bibliometric research has sought to map trends and intellectual structures in mathematics education. However, most existing bibliometric studies have either examined the field at a general level or focused on limited affective constructs and relatively short time spans (Zawacki-Richter et al., 2020; Donthu et al., 2021). While these studies provide valuable insights into publication growth, collaboration patterns, and dominant themes, they often lack a long-term, psychologically integrated perspective that captures the thematic evolution of affective factors in mathematics education (Donthu et al., 2021). The present study positions itself as an extension and advancement of this literature by systematically synthesizing affective research in mathematics education over an extended temporal window and by integrating educational and psychological perspectives within a unified bibliometric framework.

Accordingly, the importance of this study lies in its holistic examination of this complex structure by bringing together seven distinct thematic focuses that have emerged at the intersection of mathematics education and educational psychology. By adopting a longitudinal and multidimensional bibliometric approach, the study aims to systematically reveal the critical role of affective factors in mathematics achievement and to provide researchers and educators with a comprehensive perspective on the field’s evolution. Furthermore, by examining the interaction between affective dimensions and emerging themes such as technology use and instructional materials, the study seeks to offer insights into contemporary educational challenges. In this context, the findings are expected to inform the design of innovative pedagogical approaches and intervention programs that explicitly incorporate affective processes into mathematics education.

In this study, topic modeling was used to reveal thematic developments and patterns of academic interest over time on a defined research topic. Such methods allow for a comprehensive and systematic review of research conducted in a specific field. Through topic modeling and trend analysis, it is possible to track developments in the field over time, identify emerging themes, and analyze shifts in research priorities. The Orange software is used for this purpose. This software first classifies the keywords of article collections using machine learning methods (Demšar and Zupan, 2013). In this way, articles are grouped under common topics. This approach also facilitates the identification of research areas that have been insufficiently researched or neglected.

Methodologically, this study is positioned at the intersection of bibliometric analysis, science mapping, and text-mining–based topic modeling. Unlike traditional bibliometric studies that primarily focus on citation counts, co-authorship networks, or keyword frequencies, the present study adopts a longitudinal, topic-oriented approach to examine the thematic evolution of affective factors in mathematics education. By integrating PRISMA-guided systematic data collection with Latent Dirichlet Allocation (LDA) and trend topic analysis, the study moves beyond descriptive bibliometrics and provides an interpretable mapping of how research themes have emerged, diversified, and shifted over time.

First, when considering the data obtained on search terms, the thematic distribution of research in the field of psychology in mathematics education provides important clues about the current state of the field and future directions. Frequency analyses reveal that the studies exhibit a largely asymmetric distribution. The term “mathematics anxiety” (1197) having by far the highest frequency indicates that the field is largely oriented toward a problem-focused paradigm. This suggests that mathematics anxiety is perceived as a critical psychological barrier for both students and educators and has established a strong research tradition at the intersection of clinical psychology and educational psychology. Structures with medium frequencies, such as “mathematics self-concept” (207), “mathematical self-efficacy” (137), and “mathematics motivation” (134) indicate that social cognitive theory and self-theories hold an important place in mathematics education, and that individuals’ cognitive representations and motivational processes related to mathematics remain on the research agenda.

However, low-frequency terms reveal significant gaps in the field. In particular, concepts centered on positive psychology, such as “mathematics enjoyment” (15), “mathematics curiosity” (2), and “mathematics flow” (0), appear to have been studied quite limitedly. This situation shows that research has largely focused on negative emotions and cognitive processes, while positive emotional experiences and the enjoyment of learning have not been sufficiently investigated. Similarly, the low frequency of social psychological factors such as “sense of belonging in mathematics” (7) indicates that the social and cultural dimensions of mathematics learning have been neglected. Furthermore, the lack of metacognitive processes such as “epistemological beliefs about mathematics” (8) and integrated theoretical frameworks such as the “affective-motivational model” (0) suggests that the field exhibits a fragmented and scattered structure.

The limited number of intervention and application-focused studies is also noteworthy. The low frequency of terms such as “mathematics intervention” (55) and “mathematics resilience” (9) indicates shortcomings in translating basic research findings into practice and in designing resilience development programs. In light of these findings, it can be said that the field of mathematics education psychology needs a more balanced and inclusive approach.

Research on affective factors in mathematics education between 1978 and 2025 reveals significant evolutionary patterns. A comprehensive review of 2,587 publications through thematic modeling and temporal analysis shows notable transformations in both the volume and thematic orientation of research focus. The findings presented below cover seven distinct thematic clusters identified using the Latent Dirichlet Allocation (LDA) method, as well as the developmental trajectories of these clusters over five-year periods and the structural relationships between research areas revealed by hierarchical clustering and multidimensional scaling analyses. The analysis reveals that teacher-focused research and math anxiety have emerged as dominant themes in recent years, while also identifying underdeveloped research areas that hold significant opportunities for future academic research.

Table 2 shows the development of articles published on affective factors in mathematics education between 1978 and 2025 and their distribution according to seven main topics.

Looking at the “Total” row of the table, it can be seen that studies related to the affective domain in mathematics education have been steadily and rapidly increasing; particularly in the recent period (2020–2025), with a total of 1,345 articles, approximately 52% of all articles have been published. This shows that the topic has become one of the most interesting areas in the academic community today.

There are significant differences in research intensity between topic headings across all time periods.

Most Intensively Studied Topics Topic 2 (Factors Affecting Affective Factors—997 articles), Topic 5 (The Effect of Affective Factors on Achievement—514 articles), and Topic 6 (Anxiety in Mathematics Education and Instruction—407 articles). This intensity shows that researchers have focused primarily on investigating what affects affective variables, how they relate to success, and the problem of anxiety.

The least studied topic is Topic 1 (Technology and Materials in Studies Related to Affective Factors in Mathematics Education—Total: 42 articles). This low number of articles is closely related to the unique focus of the topic. Topic 1 brings together experimental and situational studies that focus on the formation and change of students’ affective characteristics and examine the application methods, effects, and effectiveness of digital technologies, learning materials, and pedagogical tools in this process. The main focus of these studies is technology; it involves technology in both the development and data collection and analysis stages. Due to this specific focus, it is logical that the number of articles in Topic 1 is lower than in other topics because technology is generally associated more with cognitive abilities and achievement, and pure affective skills are not the primary focus of technology researchers. Therefore, the number of rigorous, technology-centered studies focusing on affective outcomes in this area is still limited.

According to the findings of the hierarchical clustering analysis (Figure 4), the topics examined were grouped into two main clusters: Cluster C1 (Topics 2, 4, 5, and 6) and Cluster 2 (Topics 1, 3, and 7). The order of convergence of the main C1 cluster reflects the fundamental research focus in the affective domain. The early and high similarity convergence of Topic 4 (Teachers and Teaching) and Topic 6 (Mathematics Anxiety), which form the basis of the cluster, indicates that the majority of the studies focused on the direct relationship between the anxiety phenomenon and the pedagogical role of teachers. The subsequent inclusion of Topic 5 (Student Achievement) in this relationship reinforces the significance of treating student achievement as the primary outcome variable in these studies. Topic 2 (Factors Affecting Affective Factors), the last component of the cluster, forms the most distant connection because it examines general variables affecting affective factors; this shows that Topic 2 focuses on variables that predict affective outcomes, unlike the other topics. The C1 cluster generally examines the central role of affective state in mathematics education within the educational and teaching processes and, in this respect, focuses directly on the pedagogical context.

The second cluster does not show as high a degree of similarity as C1, but it does exhibit a meaningful relationship within itself. In this cluster, Topic 3 (Demographic Variables) and Topic 7 (Family Influence) are primarily combined. The proximity of these two topics stems from their examination of the strong relationship between affective outcomes and the individual background (demographic variables) and the closest environmental factor, family influence. Topic 1 (Technology and Materials), on the other hand, is positioned further away from the other topics due to its focus on technology use, which can be included up to the analysis stage of the studies. The common point of this cluster is that it examines the contextual relationship of these three factors with affective factors in the educational environment, rather than focusing directly on education and teaching processes.

Multidimensional scaling (MDS) analysis (Figure 5) visualizes the relationships between topics by positioning them on a two-dimensional plane through color transitions. Similarly, hierarchical clustering results also support the structure observed in the MDS map. In the graph, Topic 6, Topic 5, Topic 4, and Topic 2 are located close to each other and share a similar color spectrum. These topics together form cluster C1, representing studies focusing on the impact of teaching, learning, and success on affective factors.

In contrast, Topic 1, Topic 3, and Topic 7 form a distinct cluster structure. Topic 3 and Topic 7, in particular, are closely positioned and include studies related to family and demographic variables. Topic 1, on the other hand, is located further away from all other topics and represents studies focusing on the use of technology in mathematics education in different contexts.

When hierarchical clustering and multidimensional scaling (MDS) results are evaluated together, it is seen that studies related to affective factors in mathematics education are grouped around two main thematic axes. The first axis (Topics 2, 4, 5, 6) covers affective variables related to teaching, learning, and achievement, while the second axis (Topics 1, 3, 7) highlights contextual factors such as technology, demographic characteristics, and family. The spatial differentiation observed in the MDS map confirms the thematic clustering identified in the dendrogram analysis.

The word clouds and weight graphs (Figure 6) visualized with the keywords obtained as a result of topic modeling (Table 2) confirm the thematic focus of the seven identified topics.

Topic 1: Technology and Materials in Studies Related to Affective Factors in Mathematics Education clearly focuses on technology integration, as indicated by the keyword “computer” and the inclusion of various technological tools such as “device,” “calendar,” and “whiteboard” in the weight graphs (Figure 5). However, the fact that the keywords “teach” and “student” appear at the end of the list suggests that technology itself is the primary focus of these studies, with teaching or learning outcomes positioned as secondary objectives (Table 3).

Topic 2: Factors Affecting Affective Factors in Mathematics Education includes words that point to teaching and learning outcomes, such as “student,” “school,” “learn,” “teach,” and “achieve,” along with different affective factors (“attitude,” “anxiety,” “self”) related to different affective factors. This combination reveals that the basis of the topic is to examine the complex interaction of affective variables on learning and teaching processes.

Topic 3: The Relationship of Demographic Variables to Affective Factors in Mathematics Education includes words related to social identity and structure, such as “gender,” “women,” “ethnic,” and “stereotype.” This shows that it examines the relationship between affective factors and social status and demographic characteristics. Furthermore, it is noteworthy that affective components such as “interest” and “mindset” are at the forefront in this topic, rather than general anxiety.

Topic 4: The relationship between teachers and teacher candidates and affective factors in mathematics education is characterized by the words “teacher” and “preservice” being the most dominant words in both the word cloud and weight graphs. While words indicating pedagogical action, such as “instruction,” are prominent, “belief” is dominant as an affective component. This shows that the studies primarily focus on teachers’ and teacher candidates’ beliefs and perceptions of self-efficacy regarding teaching.

Topic 5: The title “The Effect of Affective Factors in Mathematics Education on Student Achievement and Learning” indicates that the focus is on outcomes for students, as it includes the keywords “student” and “achieve.” Cognitive emotions such as “self-concept,” “attitude,” and “belief” are prominent in this regard.

Topic 6: Anxiety in Mathematics Education-Teaching, as the name suggests, includes “anxiety” as the fundamental affective factor, indicating that this emotion forms the main axis of related studies. Anxiety is examined based on its relationship with different cognitive and behavioral elements.

Finally, Topic 7: The family’s influence on affective factors in mathematics education, with the words “children” and “early” along with the word “parent,” suggests a focus on the effect of family relationships on affective factors, particularly in the preschool and early childhood periods. Anxiety is also seen to be a prominent factor in this regard.

An examination of the graphs (Figure 7) clearly shows that academic interest in affective factors in mathematics education has increased steadily and rapidly from 1978 to 2025. Although the growth trends for all topics are positive, this growth rate and focus of interest show significant differences over time. The turning point in the number of articles began in Topic 5 during the 2004–2008 period, while other mainstream topics (Topics 2, 3, 4, 6, 7) experienced their major leap starting in the 2009 period. These mainstream topics, namely factors affecting affective factors (Topic 2), predicting success (Topic 5), and math anxiety (Topic 6), have the highest growth rates and form the main body of the field. On the other hand, Topic 1 (Technology and Materials in Studies on Affective Factors in Mathematics Education) has the lowest growth rate (m = 2.1) compared to all other main topics. Topic 1’s low performance can be attributed to the central role of technology in its definition. This topic places technology at the center as both a tool and an analysis method for understanding and developing affective characteristics. However, since cognitive abilities are generally the primary focus of technology, technology-based studies focusing solely on affective skills have failed to attract the main interest of researchers working in the field of mathematics education, and interest has shifted to other topics. This situation suggests that technology-based studies directly related to mathematical affective skills have shifted their focus to technology experts outside of mathematics education or to cognition-focused research, and that interest in this specific area has relatively declined. On the other hand, Topic 4 (Teachers), with its increase after 2014, reveals that the importance of teachers’ own emotional states has grown exponentially in recent years.

This analysis examines the relative percentage of each topic within the total publication volume, based on the periodic distribution of articles published between 1978 and 2025 (Figure 8). This reveals the evolution of academic interest in emotional factors in mathematics education over time. In the early period (1978–1993), Topic 2 (Factors Affecting Emotional Factors) and Topic 5 (The Effect of Success) were clearly dominant among the topics that formed the basis of the field. These two topics have long been prominent in the literature because they focus on both basic psychological processes () and the affective aspects of performance-based learning outcomes. However, the negative slope coefficients (m₂ = −2.453; m₅ = −1.329) indicate that the relative shares of these topics have decreased over time. This decrease is more indicative of research saturation in these topics and a shift in researchers’ interests toward more specific subfields than a decline in interest in the field. In contrast, Topic 4 (Teachers/Teacher Candidates) shows a remarkable increase over time. This area, which stands out as the topic with the highest positive slope with a value of m₄ = +2.2882, has shown strong growth, particularly since the 2000s, focusing on the effects of teachers’ beliefs, attitudes, and anxiety levels on student achievement and motivation. This indicates a shift in the focus of affective research in mathematics education from a student-centered structure to a teacher-centered structure. Similarly, Topic 6 (Mathematics Anxiety) also shows a positive slope with a value of m₆ = +0.5303, exhibiting a rapid rise, especially in the post-2010 period (2014–2025). This trend indicates that math anxiety has become a central problem area for both students and teachers, and that awareness of this issue has increased significantly in the academic community. On the other hand, Topic 1 (Technology and Materials) shows an almost stagnant trend (m₁ = +0.0195), failing to increase its relative interest over the period from 1978 to 2025. Although the absolute number of articles has increased, this increase has been parallel to the overall growth in publications. Therefore, technology-focused affective research has shown development proportional to the overall momentum of the field, but not exceeding it. This situation suggests that the association of technology with affective factors remains an underdeveloped subfield. In conclusion, throughout the period 1978–2025, technology-based and success-oriented studies in mathematics education research on affective factors have reached a saturation point, while teacher-themed and anxiety-oriented research orientations have rapidly increased. This picture shows that the field is evolving into a broader and more multidimensional structure by turning to new emotional dimensions and actors in its maturation process.

This bar chart (Figure 9) summarizes the relative interest dynamics (topic slope coefficients) of research on affective factors in mathematics education literature between 1978 and 2025. The graph clearly shows that the academic focus in the field has shifted over time from student outcomes to teaching actors and specific problem-solving.

The most pronounced upward trend is observed in Topic 4 (Teachers/Teacher Candidates) and Topic 6 (Mathematics Anxiety). Topic 4 having the highest positive slope indicates that affective research is placing greater emphasis on the role of the teacher and that interest in the field is shifting toward the impact of teaching factors on affective skills, as well as student performance. This situation reveals that educators’ affective competencies (belief, self-efficacy, anxiety) are accepted as a central variable for the quality of the learning environment and student motivation. The rise in Topic 6 confirms that math anxiety is increasingly recognized as a fundamental and priority issue in the academic community and that there is a growing need for solution-oriented work in this area.

In contrast, Topic 2 (Factors Affecting Affective Factors) and Topic 5 (The Effect of Success), which were dominant research areas in the early periods, have the largest negative slope values. This negative trend indicates that, despite the absolute increase in the number of articles, research saturation has been reached in these fundamental topics and relative interest in the field has declined. Consequently, these topics are now struggling to attract the primary interest of researchers, indicating that resources and interest are shifting toward more specific and application-centered emerging topics (Topic 4, 6). Other topics (Topics 1, 3, 7) follow a more stable trajectory, showing growth below or in line with the overall growth in the field.

The findings of this study reveal that the academic research agenda on affective factors in mathematics education has undergone significant evolution from 1978 to the present day, and that this evolution is consistent with broader paradigmatic shifts in the field. The most striking finding is that, despite steady and exponential growth in the absolute number of articles, there has been a marked shift in the thematic focus of relative academic interest. The decline in the relative share of broad and fundamental psycho-educational topics, which were dominant in the early period, suggests that a kind of saturation has been reached in these areas. This situation can be interpreted as an indicator of the field’s maturation; researchers are now turning to more specific and contextual questions such as “in whom, how, and depending on what are these factors shaped?” rather than “are affective factors important?” (Leder and Forgasz, 2018; Grootenboer et al., 2015). Recent bibliometric reviews confirm that mathematics education research has increasingly shifted toward context-sensitive and mechanism-oriented questions, reflecting a more advanced stage of disciplinary development (Donthu et al., 2021). This transition signals a new phase in mathematics education research that could be called the third wave (Gomez, 2017).

The present study contributes uniquely to this literature by empirically demonstrating this paradigmatic transition through long-term trend topic analysis, offering longitudinal evidence that complements and extends earlier cross-sectional or short-period bibliometric studies.

The strongest evidence for this trend is the rapid increase in studies focusing on the affective factors of teachers and teacher candidates, indicating a systematic shift in mathematics education research from student-centered to teacher-centered perspectives. The literature consistently shows that teachers’ mathematical beliefs, anxieties, and self-efficacy shape not only their instructional practices but also students’ affective profiles, classroom experiences, and academic achievement (Peters, 2022). In particular, teachers’ mathematics anxiety may be transmitted to students through classroom interactions and emotional climate (Bekdemir, 2010; Beilock et al., 2010). Recent large-scale studies further demonstrate that teacher affect functions as a mediating variable between instructional quality and students’ emotional engagement (Zhao, 2024).

From a practical standpoint, this finding highlights teacher affect as a critical leverage point for intervention, suggesting that professional development programs targeting teachers’ affective competencies may yield indirect but substantial benefits for student engagement and achievement.

Recent research highlights the potential to further enrich this line of inquiry by incorporating growth mindset and computational thinking. Teachers’ growth mindset beliefs influence how mistakes, effort, and persistence are framed in the classroom (Dweck, 2006), while orientations toward computational thinking shape how problem-solving and digital tools are integrated (Wing, 2006; Weintrop et al., 2016). Emerging studies indicate that embedding these constructs jointly in teacher education reduces student anxiety and strengthens mathematical agency (Looi, 2024). However, the limited number of such integrative studies points to a clear research gap: the need for theoretically grounded models that explicitly connect teacher affect, instructional cognition, and student emotional outcomes.

Similarly, the increased focus on math anxiety reflects its reconceptualization as a multidimensional phenomenon intersecting with neuroscience and educational policy. Neurobiological evidence demonstrates its negative effects on working memory (Ramirez et al., 2018), reinforcing the urgency of evidence-based interventions (Dowker et al., 2016; Carey et al., 2016). Recent interdisciplinary studies integrate neurocognitive and affective data to design targeted interventions (Yu, 2023). Despite this progress, intervention research remains unevenly distributed across educational levels and cultural contexts, revealing another important gap for future inquiry.

On the other hand, studies addressing technology and instructional materials occupy a relatively limited position within the affective research agenda. While this may appear counterintuitive given digital transformation in education, it reflects the historical prioritization of cognitive outcomes in technology research (Hwang et al., 2015; Aliyu et al., 2021). Recent reviews emphasize that affective outcomes of educational technologies remain conceptually underdeveloped and methodologically challenging, especially in AI-supported environments (Gqoli and Baidoo, 2025). This finding should be interpreted cautiously, not as a lack of relevance, but as evidence of an underexplored and methodologically demanding research frontier. Well-theorized empirical studies are needed to clarify the conditions under which AI-supported environments reduce math anxiety and foster positive mathematical identities (Elsayed and Abdo, 2023).

Finally, the cluster centered on demographic variables and family influence underscores the sociocultural embeddedness of affective development. Mechanisms such as stereotype threat (Steele, 1997; Spencer et al., 2016) and intergenerational transmission of math anxiety (Maloney et al., 2015; Sweeney and Wilson, 2023) operate differently across contexts (El Chaabi and Younes, 2025). These results highlight a persistent gap in culturally responsive and equity-oriented affective research, particularly in underrepresented regions and populations.

This asymmetric distribution in the research agenda further reveals conceptual blind spots. Positive psychological constructs (enjoyment, curiosity, flow) and social factors (sense of belonging) remain underrepresented, limiting the explanatory power of dominant models (Pekrun and Linnenbrink-Garcia, 2024). Likewise, epistemological beliefs and metacognition are insufficiently integrated, despite their central role in linking cognition and affect (Hofer and Pintrich, 1997; Muis and Franco, 2009). The lack of integrated affective–metacognitive intervention studies represents a critical disconnect between theory and classroom practice.

This study examined research trends in affective factors in mathematics education between 1978 and 2025 using trend topic analysis and revealed a dynamic but asymmetrical evolution of the field. The systematic shift from general themes to specific and contextual topics reflects increasing conceptual sophistication, yet the dominance of deficit-oriented constructs (particularly mathematics anxiety) indicates a problem-centered research paradigm.

In contrast, the marginal presence of positive psychology constructs such as enjoyment, curiosity, and flow highlights a significant imbalance. Although thematic clustering reveals meaningful structural patterns, the low representation of social and metacognitive factors indicates that the field remains conceptually fragmented rather than theoretically integrated.

The unique contribution of this study lies in its long-term, data-driven mapping of these imbalances, providing empirical evidence of not only what the field has prioritized, but also what it has systematically overlooked over nearly five decades.

To advance the field, future research must rebalance thematic priorities by expanding work on positive affective experiences and developing comprehensive frameworks that integrate affective, cognitive, metacognitive, and social dimensions. Qualitative and mixed-method studies are particularly needed to capture the lived emotional experiences of learners and teachers.

Experimental research at the intersection of technology and affective factors should be strengthened through theoretically grounded designs. AI-based adaptive systems, augmented reality, and immersive environments hold promise, but their affective impact must be tested rigorously and cautiously.

From a policy and practice perspective, the findings call for the explicit integration of affective goals into teacher education and curriculum design. Supporting teachers’ affective competencies, embedding affective objectives in curricula, and implementing early screening mechanisms for math anxiety can translate research insights into sustainable educational change.

Finally, while this study offers a comprehensive longitudinal overview, its reliance on trend topic analysis limits insights into intellectual structures and collaboration patterns. Future bibliometric studies integrating co-citation, bibliographic coupling, and keyword co-occurrence analyses can extend this work by revealing theoretical lineages and emerging research fronts. Such multi-method approaches will enhance the strategic development of a more balanced, inclusive, and impactful affective research agenda in mathematics education.