Teaching self-efficacy of graduate student instructors: Exploring faculty motivation, perceptions of autonomy support, and undergraduate student engagement

International Journal of Educational Research 98 (2019) 91–105

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International Journal of Educational Research journal homepage: www.elsevier.com/locate/ijedures

Teaching self-efficacy of graduate student instructors: Exploring faculty motivation, perceptions of autonomy support, and undergraduate student engagement

T

⁎

Carlton J. Fonga, , Jendayi Bizelle Dillardb, Molly Hatcherc a

Department of Curriculum and Instruction, Texas State University, United States Department of Educational Psychology, The University of Texas at Austin, United States c Faculty Innovation Center, The University of Texas at Austin, United States b

A R T IC LE I N F O

ABS TRA CT

Keywords: Graduate student instructors Teaching assistants Teaching self-efficacy Undergraduate student engagement Postsecondary education Faculty motivation

In the U.S., graduate student instructors teach a substantial percentage of undergraduate courses. Teaching motivation is an important predictor of high-quality teaching; thus, understanding the motivations and beliefs of graduate student instructors is essential for undergraduate student success. Graduate students also form the pool from which faculty members are selected, so the trajectories of emerging faculty are often set during these formative teaching experiences. Our study explored antecedents of teaching self-efficacy for 98 graduate student instructors from STEM, humanities, and social science disciplines. We found that the number of semesters completed in graduate school and being in a non-STEM field were positively associated with teaching self-efficacy for instructional approaches and teaching self-efficacy for learning environment, respectively. Additionally, we found that teaching self-efficacy along with autonomy-supportive instruction was positively related to undergraduates’ classroom engagement (n = 2623). Relations between perceptions of autonomy-support and classroom engagement were moderated by teaching self-efficacy; this moderation was more pronounced for STEM contexts. Implications for research and practice are discussed.

1. Introduction A central goal of postsecondary education is to provide high-quality instruction that promotes undergraduate students’ engagement and learning. Because curricular and pedagogical decision-making in higher education is relatively autonomous and dependent on individual instructors’ teaching approaches, understanding teaching beliefs and motivations of faculty members is essential. Postsecondary instructors establish an enduring teaching style, set of teaching skills (Boice, 1996), and professional identity (Svyantek, Kajfez, & McNair, 2015) during their early teaching experiences (Morris & Usher, 2011). Most U.S. faculty members gain their initial teaching experiences as graduate student instructors (GSIs), postsecondary teachers who have completed bachelor’s degrees and are pursuing graduate education. Graduate teaching experiences, as limited as they may be, remain the major preparation for future faculty teaching responsibilities (Major & Dolly, 2003; Nyquist, Abbott, Wulff, & Sprague, 1991). Additionally, GSIs are faculty members in their own right as

⁎ Corresponding author at: Department of Curriculum and Instruction, Texas State University, 601 University Dr., San Marcos, TX, 78666, United States. E-mail address: [email protected] (C.J. Fong).

https://doi.org/10.1016/j.ijer.2019.08.018 Received 31 January 2019; Received in revised form 15 August 2019; Accepted 28 August 2019 0883-0355/ © 2019 Elsevier Ltd. All rights reserved.

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they teach a large portion of undergraduate courses. In the U.S. alone, estimates of teaching loads for GSIs range between 25% to over 50% of undergraduate courses (Douglas, Powell, & Rouamba, 2016; Johnson & McCarthy, 2000; Jones, 1993). By examining this population, we can gain insight into teaching practices and beliefs of faculty members (Austin, 2002). Although there are many factors associated with the success of faculty members, teaching motivation is an important predictor of high-quality teaching and future engagement in professional development (Daumiller, Dickhäuser, & Dresel, 2019; Morris & Usher, 2011). In particular, teaching self-efficacy—the beliefs instructors hold about how they can influence students’ learning–is an important indicator of teaching effectiveness (Fong, Gilmore, Pinder-Grover, & Hatcher, 2019). Because teaching self-efficacy research has focused on K-12 contexts (Tschannen-Moran, Hoy, & Hoy, 1998), we wanted to extend our understanding of this construct in higher education contexts among the GSI population. Also, because graduate student teaching experiences comprise the formative period when faculty members develop their beliefs and motivations about teaching, it is important to investigate emergent teaching self-efficacy beliefs of postsecondary instructors. Therefore, in our investigation, we first explored antecedents of GSIs’ teaching selfefficacy. Second, we examined how teaching self-efficacy along with perceived autonomy-supportive teaching influence undergraduate engagement.

2. Literature review In the following sections, we first review the literature on GSIs. We then introduce our theoretical framework and teaching selfefficacy as our focal construct. Lastly, we discuss the role of perceived autonomy-support and the outcome undergraduate classroom engagement.

2.1. Graduate student instructors Although GSIs have a wide range of instructional responsibilities in U.S. postsecondary institutions, there are three broad categories: non-teaching, adjunctive, and full (Prieto & Meyers, 1999). Complementing the instruction of full-time faculty members, nonteaching GSIs primarily grade assignments or respond to undergraduate student queries. In contrast, adjunctive GSIs collaborate with a full-time faculty member to co-teach a course. Full GSIs serve as the main instructor for a lab or discussion section. They engage in various teaching activities including developing lectures and evaluating undergraduate student learning. Participants in the present study were full GSIs. GSIs constitute a significant subsection of university instructors. Although part-time faculty members made up the greatest proportion of the academic labor market in 2015 (40%), GSIs comprised 14% of the academic labor force, more than full-time tenuretrack faculty members (8%) and comparable to full-time non-tenure-track faculty members (American Association of University Professors, 2017). GSIs not only comprise a substantial share of academic laborers but also, as they graduate, become faculty members themselves. GSIs play a critical and unique role in undergraduate education qualitatively as well as quantitatively. For example, in a study of undergraduates’ perceptions of instruction given by GSIs versus professors (Kendall & Schussler, 2012), graduate students were more likely to be described as nervous or uncertain compared to full-time faculty members. GSIs were also described as interactive and engaging, whereas faculty members tend to be perceived as distant and strict. These findings are notable as they captured an important aspect of graduate teaching: while undergraduates perceived GSIs as being less confident and self-efficacious than their professors, they also perceived them as more willing to employ interactive and engaging teaching techniques. Undergraduates also reported greater gains in content knowledge when GSIs were supportive of their learning (Wheeler, Maeng, Chiu, & Bell, 2016). In the U.S., teaching is an essential component of doctoral education; in fact, 94% of U.S. doctoral students in STEM fields have held teaching appointments (Connolly, Savoy, Lee, & Hill, 2016). Graduate teaching experiences are often the main forms of preparation graduate students receive in their pursuit of academic careers and the professoriate (Torvi, 1994). Their time in graduate school may be the only opportunity faculty members receive some formal pedagogical training (Judson & Leingang, 2016; Tanner & Allen, 2006). Unfortunately, many graduate students (as well as full-time faculty members) lack adequate training and skills to be effective postsecondary instructors (Roche & Marsh, 2000; Wankat, 1999). This lack of experience and preparation is often associated with anxiety and a lack of confidence about their teaching (Prieto & Altmaier, 1994). For GSIs, this lack of confidence in teaching may not only hinder undergraduate student learning but also dampen their pursuit of future teaching positions as faculty members (Austin, 2002). In fact, a lack of teaching self-efficacy may cause graduate students to not pursue the professoriate and leave academia entirely (Woolfolk Hoy, 2004). Therefore, the degree to which graduate students feel confident, or self-efficacious, about their teaching is an important quality to consider for their current and future instructional roles. Although our study is based in the U.S., research on U.S.-based GSIs can have global implications. The GSI role also exists in nonU.S. postsecondary institutions. In Canadian institutions, graduate students or tutors are responsible for facilitating tutorial sessions in the social sciences, supporting learning in STEM labs, and teaching their own sections of language and literacy courses in the arts and humanities. Similar tutorial models can be found in Australia, the United Kingdom, and South Africa. In addition, the ways in which GSIs develop their teaching self-efficacy and its associations with classroom engagement may inform how international faculty members can succeed as an instructor. Because a significant number of graduate students studying in the U.S. are international (Fox & Gay, 1994) and are frequently employed in university teaching roles, when some international GSIs return to their home countries, they may apply their graduate teaching experiences to their future positions. 92

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2.2. Social cognitive career theory Informed by Social Cognitive Career Theory (SCCT; Lent, Brown, & Hackett, 1994), our study examines GSIs’ teaching roles and the construct of teaching self-efficacy. This theory describes how personal characteristics, social factors, and learning experiences affect career-related choices and outcomes. Personal characteristics such as career self-efficacy can interact with other inputs from the environment and individual, which in turn affect one’s performance and vocational pursuits. Derived from Bandura (1997) general social cognitive theory (SCT), SCCT describes career self-efficacy as the set of beliefs about one’s ability to perform particular behaviors related to career goals. As a key building block of career choice and development, an individual’s career self-efficacy predicts their outcome expectancies, goals, and performance (Lent et al., 2005). Moreover, career self-efficacy serves as a positive predictor of interest, satisfaction, and persistence intentions in a career choice (Lent et al., 2015). Because of our interest in graduate student instructors, we focus on the specific career self-efficacy for the teaching profession, teaching self-efficacy. Self-efficacy is theorized to be a regulatory mechanism that influences behavior through cognitive and motivational processes (Bandura, 1997). Ross (1998) described these processes as they pertain to teaching self-efficacy and teaching behaviors. First, cognitive processes consist of increased goal adoption and commitment; thus, with regard to teaching self-efficacy, self-efficacious instructors set higher goals for themselves and their students, persisting until these goals are achieved. Second, motivational processes involve attributing behaviors to controllable aspects such as one’s effort and believing that actions will have desired effects (outcome expectations). In the teaching context, it follows that self-efficacious instructors accept more responsibility for student learning outcomes and adopt specific teaching strategies that increase student engagement. Regarding the development of self-efficacy, Bandura (1997) posited that an individual constructs self-efficacy from four main sources: mastery experiences, vicarious experiences, verbal persuasion, and psychological or physiological arousal. Mastery experiences include the personal successes and failures that inform an individual’s future success. Vicarious experiences stem from first observing performance of others who are similar in ability or status and then forming personal outcome expectancies. Verbal or social persuasions involve feedback that informs one’s sense of competence towards a task. Affective arousal refers to emotions and physiological reactions that engender pleasant or unpleasant feelings regarding a task. These four sources (when associated with teaching) are posited to inform the development of teaching self-efficacy as well. For example, mastery experiences, known to be one of the strongest predictors of self-efficacy (Usher & Pajares, 2008), occur when instructors have positive, affirming teaching experiences in the past, which bolster their confidence for future teaching. Thus, prior teaching experience is expected to be particularly formative for teaching self-efficacy. Moreover, the further a graduate student progresses through their studies, they most likely gain more content-based knowledge, observe their faculty mentors teach (vicarious experiences), and also adjust to their environment; we hypothesized that more advanced graduate students would feel more efficacious about their teaching. In addition, we expected direct instruction from a pedagogy to boost GSIs’ confidence and reduce their anxiety (affective states).

2.2.1. Teaching self-efficacy in K-12 contexts It is broadly understood that teachers need to believe in themselves as instructors to be effective in the classroom. One such belief is teaching self-efficacy, which refers to teachers’ judgment of their capabilities to bring about desired learning and engagement outcomes (Tschannen-Moran et al., 1998). Research based in K-12 contexts found strong associations between teaching self-efficacy and teachers’ use of instructionally innovative practices, professional commitment, and student achievement (Tschannen-Moran et al., 1998; Zee & Koomen, 2016). In a meta-analysis of 43 studies, Klassen and Tze (2014) found that teaching self-efficacy was strongly associated with observed teaching performance. Strong correlations emerged between teacher efficacy and an array of factors including teacher stress, student achievement, and incorporation of innovative teaching techniques (Tschannen-Moran et al., 1998). Examining antecedents of teaching self-efficacy in a study of 255 K-12 teachers, Tschannen-Moran and Hoy (2007) found that teaching self-efficacy was positively correlated with satisfaction of their past performances (or mastery experiences).

2.2.2. Teaching self-efficacy in higher education Although the majority of research on teaching self-efficacy centers around K-12 settings, teaching self-efficacy plays an important role in higher education as well (Connolly et al., 2016; Landino & Owen, 1988). Roche and Marsh (2000) argued that self-conceptual perceptions of teaching effectiveness are critical for postsecondary instructors. Conceptions of teaching self-efficacy for K-12 teachers have been successfully translated to postsecondary education (Daumiller, Grassinger, Dickhäuser, & Dresel, 2016; Daumiller, Dickhäuser, & Dresel, 2019). University instructors high in teaching self-efficacy were more student-focused and encouraged students to use a deep processing approach while learning (Gibbs & Coffey, 2004). Controlling for other covariates and motivation variables, Daumiller et al. (2016) found that faculty members’ teaching self-efficacy was positively linked with undergraduates’ perceived learning gains and instructor quality. Drawing from SCT, Morris and Usher (2011) interviewed 12 university professors to explore their sources of teaching self-efficacy. They found that both mastery experiences and verbal persuasion were key sources of teaching self-efficacy. In addition, professors’ teaching self-efficacy stabilized within the first four years of teaching, suggesting that early teaching experiences, such as those in graduate school, may be especially formative. Other research on teaching self-efficacy among postsecondary instructors highlighted the positive association between teaching experience and teaching self-efficacy (Mehdinezhad, 2012) in addition to disciplinary differences in teaching self-efficacy (Chang, Lin, & Song, 2011). Extending these findings, we were interested in examining teaching self-efficacy of GSIs and the role of experience and disciplinary differences as well. 93

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2.2.3. Teaching self-efficacy of graduate student instructors Within the relatively small research base on teaching self-efficacy in higher education, an even smaller subset has examined the teaching self-efficacy of GSIs. GSI teaching self-efficacy has been linked with increased undergraduate student academic performance (Braskamp, Caulley, & Costin, 1979). College students perceive GSIs with high teaching self-efficacy as effective in the classroom, supportive of personal relations, and enthusiastic while teaching (Grush & Costin, 1975). Moreover, developing teaching self-efficacy for graduate students is especially critical as it can have long-term consequences when they transition into the professoriate (Oleson & Hora, 2014). Interviewing new, full-time faculty members, Major and Dolly (2003) found that teaching mentorship and teaching experiences in graduate school shaped their teaching self-efficacy. Research on GSIs has indicated that teaching experience and pedagogical training are important antecedents to teaching selfefficacy (DeChenne, Enochs, & Needham, 2012; DeChenne, Koziol, Needham, & Enochs, 2015; Prieto & Altmaier, 1994). Because of the positive effects of teaching self-efficacy, teaching trainings for GSIs often target teaching self-efficacy as one of the main outcomes (Fong et al., 2019). Although there is a growing body of evidence regarding GSI pedagogy training, understanding how previous GSI experiences along with pedagogy course completion relate to teaching self-efficacy is still needed. More importantly, mechanisms underlying the relationship between teaching self-efficacy and educational outcomes for undergraduates are relatively unknown. 2.3. Multidimensional nature of teaching self-efficacy In addition, the multidimensional nature of teaching self-efficacy has been well documented in prior studies and theory (Nie, Lau, & Liau, 2012). For instance, teaching self-efficacy regarding instruction should be distinguishable from teaching self-efficacy regarding classroom management and student motivation. Capturing this kind of differentiation in teaching self-efficacy dimensions was also central to our study. For GSIs, we wanted to assess two dimensions of teaching self-efficacy: (1) self-efficacy for the effective preparation and delivery of content using a variety of instructional strategies, and (2) self-efficacy for creating a positive learning climate where students feel comfortable to participate in learning activities. These dimensions mirrored two aspects found by other research of the multidimensionality of teaching self-efficacy. Namely, our study captures teaching self-efficacy for instructional strategies (found both in scales by Nie et al., 2012; Tschannen-Moran & Hoy, 2001) and teaching self-efficacy for a positive learning environment (similar to teaching self-efficacy for student engagement, Tschannen-Moran & Hoy, 2001 and teaching self-efficacy for motivational strategies, Nie et al., 2012). Teaching self-efficacy measures typically assess a third dimension of classroom or behavior management; however, classroom management is less of a concern for higher education settings compared to K-12 contexts. 2.4. Teaching self-efficacy and student classroom engagement One of the main outcomes of interest in our study was undergraduate students’ classroom engagement. Educational psychologists have described engagement as a multidimensional construct, with emotional, cognitive, and behavioral aspects (Fredericks, Blumenfeld, & Paris, 2004). Emotional engagement includes students’ social, emotional, and psychological attachments to school. Cognitive engagement typically revolves around students’ psychological investments in academic tasks, such as one’s mental effort. Behavioral engagement ranges from prosocial conduct to the amount of time spent studying or engaging in particular activities. Research has consistently underscored the importance of classroom engagement on academic achievement (Gasiewski, Eagan, Garcia, Hurtado, & Chang, 2012; Marks, 2000); however, associations between instructors’ teaching self-efficacy and student engagement are less clear. In fact, Klassen, Tze, Betts, and Gordon (2011) emphasized the need to clarify and strengthen links between teaching self-efficacy and student outcomes. Drawing from social cognitive (career) theory, Woolfolk Hoy and Davis (2005) developed a related framework exploring consequences of teaching self-efficacy for students’ beliefs and behaviors. Some of the direct consequences are structuring classroom learning to afford more time spent for students’ learning, engagement in meaningful tasks, and increased motivation, effort, excitement, and arousal. Teaching self-efficacy may also indirectly influence students’ beliefs and behaviors by enhancing students’ academic interests and modeling for students how to identify with academics. Both direct and indirect consequences over time benefit students’ situational motivation, self-regulation, and achievement. Thus, building off this framework and tenets of SCCT, we examined associations between GSIs’ teaching self-efficacy and classroom engagement. Perhaps GSIs who felt particularly efficacious in employing effective instructional strategies could facilitate engagement leveraging innovative, inclusive and engaging instructional techniques. GSIs with high efficacy in facilitating a positive learning environment might enhance engagement by removing affective and emotional barriers to classroom participation. For the focus of our study, we were interested in the dynamic relation between teaching self-efficacy and autonomy-supportive teaching practices. 2.5. Teaching self-efficacy and autonomy-supportive teaching practices Along with instructors’ levels of teaching self-efficacy, the ways in which instructors enhance their undergraduate students’ motivation through teaching practices are essential for postsecondary instruction. Thus, one mechanism by which teacher selfefficacy influences student engagement may be the use of autonomy-supportive teaching practices, an instructor’s interpersonal behaviors that involve and nurture inner motivational resources of those they teach (Reeve & Jang, 2006; Reeve, 2009). Autonomysupportive instructors identify students’ motivational resources and facilitate learning activities in which students align such resources with the task at hand (Reeve, Jang, Carrell, Jeon, & Barch, 2004). Autonomy-supportive practices are associated with a wide 94

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range of student outcomes, including enhanced academic engagement (Reeve et al., 2004), creativity (Koestner, Ryan, Bernieri, & Holt, 1984), conceptual understanding (Grolnick & Ryan, 1987), motivation (Deci, Nezlek, & Sheinman, 1981), and college students’ academic performance (Fong & Zientek, 2019). Because of the manifold benefits associated with autonomy-supportive teaching practices, we wanted to examine how students’ perceptions of autonomy-support from their GSIs would be associated with their classroom engagement. We were interested in whether autonomy-supportive teaching practices would either mediate or moderate the influence of teaching self-efficacy. On one hand, a mediation model would support Woolfolk Hoy and Davis (2005) framework, which suggested that teaching self-efficacy has consequences for teachers’ beliefs and behaviors. One indirect consequence identified by the framework is being supportive of students’ autonomy. Perhaps instructors with higher levels of teaching self-efficacy teach in more motivating and engaging ways, but this has been mostly examined in K-12 settings (Ashton & Webb, 1986; Caprara, Barbaranelli, Steca, & Malone, 2006). On the other hand, the mediation model approach is limited given a lack of evidence supporting the link between teaching selfefficacy and autonomy-supportive practices as perceived by the students themselves (Domen, Hornstra, Weijers, van der Veen, & Peetsma, 2019). Research has revealed moderate associations between teacher-reported teaching self-efficacy and autonomy-supportive teaching (rs = .32–.33, Hascher & Hagenauer, 2016; r = .30, Leroy, Bressoux, Sarrazin, & Trouilloud, 2007), but little is known about student-perceived autonomy-support and its associations with teaching self-efficacy. Given that autonomy support is theorized by Woolfolk Hoy and Davis (2005) to be only indirectly related to teaching self-efficacy, a moderation model may be more suitable. Specifically, teaching self-efficacy and student-perceived, autonomy-supportive practices may be orthogonal, suggesting that instructors may feel self-efficacious about their teaching but may not be perceived to be autonomy-supportive, or vice-versa. That being said, perhaps the synergistic or multiplicative influence of a highly self-efficacious instructor who is also autonomysupportive may enhance student engagement. Thus, we took an exploratory approach to examine both moderation and mediational models. 2.6. Present study Because of important connections between GSIs’ teaching experiences and their effectiveness as faculty members in the future, we first investigated the antecedents of teaching self-efficacy for GSIs, or in some respects, emerging faculty members. The question still remains regarding how GSIs develop their teaching self-efficacy. Also, as an exploratory move, we tested if teaching self-efficacy may differ by discipline (STEM vs. non-STEM). In light of these issues and hypotheses, our first research question was: What GSI characteristics, namely teaching experience, length in graduate school, pedagogy training, and discipline, are associated with GSIs’ teaching self-efficacy? In addition, teaching self-efficacy is frequently linked with positive student outcomes, but little is known about the connection between GSI teaching self-efficacy and undergraduate classroom engagement. Thus, we wanted to examine how teaching self-efficacy relates to undergraduate classroom engagement. We also explored whether autonomy-support perceived by undergraduate students would mediate or moderate the relation between self-efficacy and classroom engagement. Thus, our second research question was: How does GSI teaching self-efficacy relate to undergraduates’ level of classroom engagement, and is this relationship mediated or moderated by undergraduates’ perceived autonomy support? Our hypothesis was that teaching self-efficacy would be positively associated with classroom engagement; however, given the exploratory examination of autonomy-support as a potential mediator or moderator, we had no prior hypotheses. For both research questions, we were interested in the multidimensional nature of teaching self-efficacy, acknowledging that teaching consists of multiple facets and dimensions (Nie et al., 2012). Thus, we measured two dimensions of teaching self-efficacy for GSIs: instructional approaches and learning environment. 3. Method 3.1. Context The study occurred in a large public, research-intensive university located in the southwest U.S. Similar to other U.S. higher education institutions, graduate students who are either pursuing a master’s or doctoral degree are typically employed by the university for half-time appointments. Whereas some graduate students work as research assistants, a large portion of graduate students work in teaching positions, especially those in the humanities and social sciences. GSIs mainly teach discussion or laboratory sections which complement a larger lecture course given by a full-time faculty member. The discussion or laboratory sections are typically weekly sessions during which instructors facilitate discussions and applications of the course material with roughly 20–30 undergraduate students. 3.2. Participants and procedures Participants were 98 GSIs who taught a laboratory or discussion class during the semester of data collection as full GSIs, serving as the independent instructor. Within our sample of GSIs, 39 of them were in a STEM (science, technology, engineering, mathematics) discipline, and 59 were studying liberal arts, which consisted mainly of humanities and social science fields. Roughly three quarters of the sample were new graduate students to the university. The majority of instructors (58.1%) reported no previous teaching experiences, and a larger percentage (83%) indicated no completion of a pedagogical training program or professional development. Other descriptive statistics for the GSI sample are provided in Table 1. Although institutional statistics indicate that 48.4% of 95

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Table 1 Descriptive Statistics and Correlations for Graduate Student Instructor Variables. Variable

M

SD

Min

Max

Skew

1

2

3

4

5

6

[1] [2] [3] [4] [5] [6]

.36 1.64 2.10 0.17 2.83 2.89

.48 2.37 2.27 .38 .47 .50

0 0 0 0 1.6 1.8

1 10 12 1 3.8 4.0

2.44 1.62 1.79 .05 −.41

1.00 −.12 −11 −.18 .02 −.33**

−.19* 1.00 .40** .38** .14 .23*

−.15 .51** 1.00 .22* .04 .12

−.18 .33* .22* 1.00 −.01 .22*

−.02 .25* .11 .02 1.00 .39**

−.34* .22* .13 .20* .44** 1.00

STEM Semesters completed Teaching experience Pedagogy course Teaching Self-efficacy: Instructional approaches Teaching Self-efficacy: Learning environment

Note. n = 98; * p < 0.05, ** p < 0.01; STEM = 1, non-STEM = 0; Teaching experience (yes = 1, no = 0); Pedagogy training (yes = 1, no = 0). Teaching self-efficacy items were scaled as 1–4 (1 = Very unconfident, 4 = Very confident). Values below the diagonal are Spearman rank correlations; values above the diagonal are bivariate correlations.

graduate students indicated their gender as female, we were unable to collect specific gender and age information on our sample. This limitation is mentioned further in our discussion. At the beginning of the fall semester, GSIs agreed to participate in a teaching assessment process through the university teaching center. Specifically, they would receive mid-semester feedback from their undergraduate students. They volunteered to join our study by completing an optional, online questionnaire that measured demographic characteristics, teaching background, and teaching selfefficacy. On average, the survey took 15 minutes to complete. In the middle of the semester after six to eight weeks of instruction, the teaching center provided facilitation of an optional, mid-semester feedback survey with undergraduate students enrolled in classes taught by the GSIs. The mid-semester survey consisted of college students’ perceptions of their instructor’s teaching practices and their self-reported engagement during class. There were 2623 undergraduate students across all the classes taught by the GSIs. Teaching center staff distributed short paper surveys during the classes GSIs taught. To avoid class disruption, they administered the 10-minute instrument during the first ten minutes. In the undergraduate survey, items assessing the value of the course were not included in the current study because these questions were written as an evaluation of the senior professor who designed the class, not the GSIs who taught the discussion and laboratory sections. 3.3. Measures 3.3.1. Teaching self-efficacy To assess the teaching self-efficacy of the GSIs, we used a scale adapted from a previous measure with sufficient psychometric properties (DeChenne et al., 2012). DeChenne et al. validated the original Graduate Teaching Assistant-Teaching Self-Efficacy Scale using exploratory factor analysis on 18 items. A two-factor solution was found which explained 46% of the variance. The two subscales were labeled as (1) self-efficacy for instructional strategies (7 items) and (2) self-efficacy for learning environment (11 items). Thus, we chose this teaching self-efficacy scale as it reflected how teaching self-efficacy can be differentiated, measuring confidence in implementing instructional approaches and creating a positive learning environment. For our study, we trimmed the number of items to 11 to reduce survey fatigue and improve completion rates of all items: five items measuring instructional strategies and six for learning environment. To validate the shortened measure, we conducted a principal components analysis with promax rotation to validate the short version. The same two-factor structure was retained, mirroring the factor structure found by DeChenne et al. (2012). To provide further evidence of the two-factor solution, we also conducted confirmatory factor analysis (CFA). Because our limited sample size in the existing study, we pulled data from another administration of the teaching self-efficacy measure. With an increased sample size of 219 GSIs, our proposed CFA model had adequate fit. Details of the PCA and CFA are presented in the online supplementary material. Participants were asked to indicate how confident they were in their ability to accomplish the stated activity in their current or future teaching roles. All items were on a 4-point Likert scale (1=Very unconfident, 2=Unconfident, 3=Confident, 4=Very confident). Measured as Cronbach’s alpha, reliabilities for teaching self-efficacy for instructional approaches and teaching self-efficacy for learning environment were .73 and .80, respectively, which are acceptable (Carmines & Zeller, 1979; Nunnally & Bernstein, 1994). Items can be found in the Appendix. Because our sample of GSIs taught a range of course subjects within the university, it was infeasible to measure domain-specific teaching self-efficacy (teaching self-efficacy for math). That being said, GSIs rated their teaching self-efficacy based on their current or future teaching roles, which would predominantly be within the same domain. For instance, a GSI in the chemistry department will only teach chemistry courses. Thus, although we did not explicitly capture domain, we maintain the multidimensional nature of teaching self-efficacy by assessing two aspects of teaching self-efficacy: instructional approaches and learning environment. 3.3.2. Perceptions of autonomy-supportive teaching strategies In a mid-semester evaluation survey designed to provide feedback to GSIs, undergraduates enrolled in sections taught by the participating instructors completed seven items, rating their instructor’s use of various autonomy-supportive teaching strategies: such as nurturing inner motivational resources (sample item: “The instructor balances following the lesson plan for our class with improvising to address students’ immediate needs, interests, and questions”); instructor-provided structure through clear communication and direction (sample item: “The way the instructor introduces new concepts supports my learning.”); and warmth and 96

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Table 2 Descriptive Statistics and Correlation for Undergraduate Student Variables.

Perceptions of autonomy-support Classroom engagement

M (SD)

Min

Max

Skew

r

4.96 (0.85) 4.83 (0.73)

1.0 1.0

6.0 6.0

−1.36 −.97

.48**

Note. n = 2,623; ** p < .01; Perceptions of autonomy support and classroom engagement were scaled as 1–6 (1 = Strongly disagree, 6 = Strongly agree). r represents the bivariate correlation between perceptions of autonomy support and classroom engagement.

involvement (sample item: “The instructor is approachable.”). All items were on a 6-point Likert scale (1=Strongly disagree, 2=Disagree, 3=Slightly disagree, 4=Slightly agree, 5 =Agree, 6 =Strongly agree). The scale items came from a standard set of items used throughout the university to evaluate classroom teaching and learning. To ensure validity of the scale, we conducted a principal components analysis (promax rotation), which indicated that a one-factor solution was most appropriate; therefore, we create a single scale score using seven items. These items corresponded to autonomysupportive teaching practices discussed by Reeve and Jang (2006). This scale score had high reliability (α = .93; Nunnally & Bernstein, 1994). See Table 2 for descriptive statistics for this scale. 3.3.3. Classroom engagement Undergraduate students also rated their level of classroom engagement (active participation, class preparation, sharing ideas, asking questions). Sample items included “I actively participate in class,” “I feel comfortable sharing my ideas in this class,” and “I prepare for class meetings.” All items were also on a 6-point Likert scale (1=Strongly disagree, 2=Disagree, 3=Slightly disagree, 4=Slightly agree, 5 =Agree, 6 =Strongly agree). Similar to the perceptions of autonomy-support scale, this scale was part of standard set of items used by the institution. We conducted a similar test for construct validity, and following principal components analysis (promax rotation), which identified a one-factor solution, we averaged the items to form a single scale score for classroom engagement. The reliability of the undergraduate student engagement scale was .81, which is acceptable (Carmines & Zeller, 1979; Nunnally & Bernstein, 1994). Table 2 presents descriptive statistics for this measure. Because students responded to items about classroom engagement and perceived autonomy-supportive practices on the same instrument, we also conducted PCA and CFA on the entire instrument to test whether the two scales (factors) were distinct. Our tests indicated that a two-factor model as planned had adequate fit; details of the analyses are provided in the online supplementary material. 3.4. Data analysis For the first research question, we conducted multiple regression to assess which factors or antecedents were associated with GSIs’ teaching self-efficacy. Specifically, we tested if domain (STEM, Liberal Arts), teaching experience, professional development, and semesters completed in graduate school were significant predictors of teaching self-efficacy. We used multiple regression to test the associations of these predictors with teaching self-efficacy jointly. We conducted two models with two different outcomes variables– teaching self-efficacy for instructional approaches (Model A) and teaching self-efficacy for learning environment (Model B)—in light of the multidimensional nature of teaching self-efficacy. In the online supplementary material, see Figure A for a visual representation of these models. For the second research question, we conducted multilevel analyses because of the hierarchical structure of our data with undergraduate students nested within their GSIs (Raudenbush & Bryk, 2002). The higher-level units (GSI) were assumed to be independently sampled with lower level units (undergraduate students) as the unit-of-analysis. This was the most appropriate method to account for the homogeneity of errors within groups. Multilevel analyses estimate and model variability in responses occurring within and between their instructors’ classes. HLM also provides a more efficient estimation of cross-level effects to examine how variables at one level affect the relationship between an independent and dependent variables at another level (Raudenbush & Bryk, 2002). The intraclass correlation was 0.10, which suggests that 10% of the variance in undergraduate classroom engagement was attributable to differences across classrooms. Similarly, we were interested in the multidimensional nature of teaching self-efficacy, so we conducted two models, one with teaching self-efficacy for instructional approaches and one with teaching self-efficacy for learning environment as part of the instructor-level predictors. Including both of these teaching self-efficacy variables in one model would reduce the power of our analyses due to the limited number of instructors in our sample. To answer Research Question 2, our main outcome was undergraduate classroom engagement, which was measured as a Level-1 undergraduate student variable. Controlling for all the variables in Research Question 1’s analysis and adding teaching self-efficacy as Level-2 variables and the perception of autonomy support as a Level-1 variable, we measured how they all relate to classroom engagement. To test the mediating or moderating role of autonomy-support, we conducted two separate analyses. First, we tested the mediation model using multilevel mediation. See Figure B for a visual representation of these models in the online supplement. We used the MLmed computational macro for SPSS which allows for a cluster-level mediator (Rockwood, 2019). Procedures for the mediation modeled followed guidance from Bauer, Preacher, and Gil (2006). If there was a significant indirect effect detected between teaching self-efficacy and classroom engagement through autonomy-support, there would be support for the mediational model. Second, to 97

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Table 3 Regression Results for Teaching Self-Efficacy for Instructional Approaches and Learning Environment. Model A - Teaching Self-Efficacy: Instructional Approaches

Model B - Teaching Self-Efficacy: Learning Environment

Variables

β

t

p

β

t

p

STEM Semesters completed Teaching experience Pedagogy training R2

.03 .29* −.02 .07 7.0%

.28 2.47 −.15 .65

.782 .015 .878 .782

−.32** .12 .01 −.10 16.2%

−3.36 1.05 .06 −1.02

.001 .298 .952 .310

Note. n = 98; * p < .05, ** p < .01; STEM = 1, non-STEM = 0; Teaching experience (yes = 1, no = 0); Pedagogy training (yes = 1, no = 0). Selfefficacy items were scaled as 1–4 (1 = Very unconfident, 4 = Very confident).

test the moderation model, we included cross-level interactions with teaching self-efficacy and perception of autonomy support to assess any moderating effects. If the interactions are significant, there would be support for a moderation model. See Figure C for a visual representation of these models. There were no missing data among the GSI variables. However, for Research Question 2, there were some missing data that were removed using casewise deletion when conducting analyses, one of the default settings in HLM 7.0, our software of choice for multilevel modeling (Raudenbush & Bryk, 2002).

4. Results 4.1. Research question 1 First, we were interested in which GSI characteristics were associated with teaching self-efficacy for instructional approaches and teaching self-efficacy for learning environment. Multiple regression results are presented in Table 3. For teaching self-efficacy for instructional approaches, results indicated that the number of semesters they had completed in graduate school was a significantly positive predictor. For teaching self-efficacy for learning environment, being in a STEM discipline was a negative predictor. This indicates that STEM GSIs felt less able to create a positive learning environment than GSIs in humanities or social sciences. Teaching experience or completion of pedagogical training were not related to either kind of teaching self-efficacy.

4.2. Research question 2 Second, we examined whether teaching self-efficacy and instructor characteristics, along with perceptions of autonomy-supportive instructional practices, predicted undergraduate students’ classroom engagement. Both multilevel models are presented in Table 4. From both models, results indicated that instructors’ disciplinary association in STEM was positively associated with classroom engagement. Both kinds of teaching self-efficacy were also positive predictors of undergraduate students’ engagement levels. At the undergraduate student level, perceptions of autonomy-supportive teaching practices were significantly and positively related to undergraduate students’ classroom engagement. GSIs’ teaching experience, completion of pedagogy training, or semesters completed in graduate school were not significant predictors of classroom engagement. Table 4 Multilevel Modeling Results for Student Engagement Using Teaching Self-Efficacy for Instructional Approaches (Model A) and Learning Environment (Model B) and Students’ Perceptions of Autonomy-Support. Model A Instructor-Level STEM Semesters completed Teaching experience Pedagogy training TSE: Instructional approaches Student-Level Perceptions of autonomy support (PAS) Cross-Level TSE: Instructional approaches x PAS TSE: Instructional approaches x PAS x STEM

Coeff.

SE

t

Model B

.682*** -.009 .004 .028 .970***

.143 .013 .013 .069 .181

4.75 −.74 .758 .411 5.37

.955***

.101

9.47

−.153*** −.031**

.036 .010

−4.23 −3.18

Instructor-Level STEM Semesters completed Teaching experience Pedagogy training TSE: Learning environment Student-Level Perceptions of autonomy support (PAS) Cross-Level TSE: Learning environment x PAS TSE: Learning environment x PAS x STEM

Coeff.

SE

t

.892*** −.004 .005 .066 .525**

.149 .014 .014 .075 .167

5.99 −.25 .335 .883 3.15

.743***

.094

7.90

−.070* −.043***

.031 .010

−2.25 −4.38

Note. *p < .05, ** p < .01, *** p < .001; STEM = 1, non-STEM = 0; Teaching experience (yes = 1, no = 1); Pedagogy training (yes = 1, no = 1). Teaching self-efficacy (TSE) items were scaled as 1–4 (1 = Very unconfident, 4 = Very confident). Perceptions of autonomy support (PAS) were scaled as 1–6 (1 = Strongly disagree, 6 = Strongly agree). 98

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Fig. 1. Plots for two-way interactions of (1) Teaching self-efficacy for instructional approaches (TSE:IA) x Perceptions of autonomy-support (PAS) and (2) Teaching self-efficacy for learning environment (TSE:LE) x Perceptions of autonomy-support (PAS). High and low levels of teaching selfefficacy and PAS were +/- 0.5 SD from the mean (mid).

4.2.1. Mediation model Results of our mediation analysis indicated that there was no significant indirect effects of both types of teaching self-efficacy on classroom engagement via perceptions of autonomy support (self-efficacy for instructional strategies: β=−.02, SE = .02, p > .05; self-efficacy for learning environment: β =−.003, SE = .02, p > .05). Examining the direct effects, we observed that autonomysupport was significantly related to classroom engagement as we found previously (β =0.45, SE = .01, p < .001), but there were no significant direct influences of either kind of teaching self-efficacy on perceptions of autonomy-support (self-efficacy for instructional strategies → perceptions of autonomy support: β=−.05, SE = .10, p > .05; self-efficacy for learning environment → perceptions of autonomy support: β=−.003, SE = .10, p > .05). 4.2.2. Moderation model Findings from cross-level interactions indicated evidence of significant moderation. Perceived autonomy-support was a positive predictor of engagement, and it also moderated the relationship between GSIs’ teaching self-efficacy and undergraduate classroom engagement. See Fig. 1 for a visualization of the interaction effect. The figure suggests that undergraduate students’ reported classroom engagement remained mostly the same regardless of the GSIs’ teaching self-efficacy when students perceived moderate to high levels of autonomy-support. However, when undergraduates perceived low autonomy-support, the relationship between classroom engagement and teaching self-efficacy increased. This pattern was found for both kinds of teaching self-efficacy. Because STEM was also a positive predictor of undergraduate students’ engagement levels, we were curious to see if the STEM context may have influenced the interaction effect discussed previously. As an exploratory step, we added a three-way interaction term (teaching self-efficacy X perception of autonomy support X STEM). In both models, the three-way interaction terms were also significant. Fig. 2 displays the interaction effects. It appears that when the perception of autonomy support is low, the relationship between classroom engagement and teaching self-efficacy increases more for STEM contexts than non-STEM contexts. This pattern was consistent for both models as well. 5. Discussion There is an ever-increasing need for improving postsecondary instruction and undergraduate student engagement in the classroom (Arum & Roksa, 2011). In the U.S., the role of GSIs who teach discussion or laboratory sections that supplement lectures and explore lecture topics in greater depth is often overlooked. Although often lacking teaching preparation, GSIs teach a large number of undergraduate students, facilitating up to half of their classes in some cases. Moreover, some GSIs are emerging full-time faculty members; thus, our study sought to explore their teaching self-efficacy and the associated antecedents and consequences of teaching self-efficacy. These concepts are essential to understanding nascent faculty motivation in higher education more broadly. We discuss our results in the following discussion. 5.1. Antecedents of teaching self-efficacy GSIs’ teaching self-efficacy was associated with two notable background characteristics. First, we found that the number of semesters a graduate student completed was positively associated with teaching self-efficacy for instructional approaches. GSIs further along in their graduate programs may have higher levels of teaching self-efficacy for instructional approaches because they are more adjusted to their positions and coursework. First-time graduate students are particularly trepidatious of teaching because they are often adjusting to a new city and campus and beginning advanced coursework (Prieto & Altmaier, 1994). Thus, completing a few semesters in graduate school may naturally make graduate students feel more comfortable on campus, and in turn, more efficacious to implement instructional approaches. Graduate students with more experience of the campus and their program may have 99

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Fig. 2. Plots for three-way interactions of (1) Teaching self-efficacy for instructional approaches (TSE:IA) x Perceptions of autonomy-support (PAS) for STEM and non-STEM and (2) Teaching self-efficacy for learning environment (TSE:LE) x Perceptions of autonomy-support (PAS) for STEM and non-STEM. High and low levels of teaching self-efficacy and PAS were +/- 0.5 SD from the mean (mid).

reduced levels of anxiety. This explanation aligns with the role of affective and physiological states for informing one’s self-efficacy, according to social cognitive career theory. Moreover, instructors with more semesters completed in graduate school may also have additional opportunities to view positive examples of effective instruction in their graduate courses. Mills (2011) observed how GSIs in the humanities modeled their teaching after the professors they were learning from, which led the graduate students to merge content knowledge with pedagogy. Through this modeling of full-time faculty members, GSIs can vicariously build their own conceptions of teaching self-efficacy. This is also in line with tenets from social cognitive career theory. Although Prieto and Altmaier (1994) indicated that teaching experience was modestly correlated with teaching self-efficacy, our findings deviated from their results. It is interesting that their study did not account for time in graduate school, which may be confounded with teaching experience (in our study, these were correlated at r = .51). Because the number of semesters completed in graduate school is linked with higher teaching self-efficacy yet participating in pedagogy courses was not, graduate programs should (re)consider the ways graduate students are trained for teaching. Perhaps pedagogy courses for our sample of graduate students were not designed appropriately and thereby failed to influence their teaching self-efficacy. For instance, a comparison of teaching development programs for GSIs revealed mixed results, highlighting the critical need to understand the best ways to prepare graduate students to teach (Fong et al., 2019). A scaffolded experience of shadowing a veteran GSI could be a valuable way for vicarious experiences to occur and teaching self-efficacy to be bolstered (Morris & Usher, 2011). Second, we found that GSIs in STEM had lower teaching self-efficacy for fostering a positive learning environment compared to GSIs in social sciences or humanities. This finding corroborates prior research that STEM learning environments are perceived as chilly and unwelcoming (Seymour & Hewitt, 1997). For instance, Hong and Shull (2010) observed an absence of positive relationships among engineering undergraduates and faculty members. Undergraduate students described their professors as “insensitive to their learning and personal needs” (p. 274). Students identified only a few professors who displayed caring qualities, such as engaging in conversations outside of class, providing support during challenging situations, or expressing concern about their professional future. It is important to note that because we did not account for gender effects with regard to teaching self-efficacy, we suggest that future research be explored to uncover potential gender effects, given the gender gap in many STEM fields.

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5.2. Teaching self-efficacy and autonomy-supportive instructional practices associated with classroom engagement A number of GSI characteristics were positively linked with undergraduate students’ classroom engagement. Being in a STEM discipline was positively associated with classroom engagement. Although STEM affiliation was negatively related to instructors’ teaching self-efficacy for learning environment, undergraduates in STEM had higher levels of engagement. One possible explanation for this finding is the nature of engagement in STEM classes in higher education. For instance, lab classes in engineering and science are interactive and provide hands-on activities, where undergraduate students are behaviorally engaged in tasks during the whole course period. In contrast, discussion classes on topics in the humanities and social sciences may not naturally generate the same degree of classroom engagement. In STEM fields, active learning and the effective dissemination of knowledge are often more valued than the affective needs of learners (Christe, 2013). We found that undergraduate students rated the instruction from STEM GSIs as high in engagement, but that the GSIs themselves felt less efficacious in creating a positive learning environment. Perhaps this can be explained by how STEM labs are structured. Lab activities are often prepared for GSIs to implement in their sections, and GSIs may not feel capable of fostering a positive learning environment within the constraints of a heavily prescribed curriculum. An alternative explanation may be that STEM GSIs may not feel self-efficacious to create positive learning environments yet are still able to engage students in the classroom. Although the predominant culture in STEM is perceived as uncaring, early intervention for GSIs may be one way to unlearn this dominant ethos (Flaherty, O’Dwyer, Mannix-McNamara, & Leahy, 2017). Training that emphasizes the affective needs of learners and the importance of the classroom environment can help prepare GSIs to create positive learning climates. These in turn may encourage undergraduate students’ additional engagement by signaling that all students are welcome and valued in the classroom. Teaching self-efficacy for both instructional approaches and learning environment were positively associated with undergraduate students’ classroom engagement levels in two separate models. These findings underscored the importance of GSIs’ teaching selfefficacy for influencing college student outcomes. This helps to strengthen the much-needed research base on links between teachers’ self-efficacy and undergraduate student outcomes (Klassen et al., 2011), especially at the classroom level where teacher characteristics play a critical role in undergraduate student outcomes. Although high teaching self-efficacy is an important outcome in its own right, it is beneficial to support the positive connection between GSI teaching self-efficacy and classroom engagement. However, future research is needed to further elucidate the specific ways self-efficacious instructors foster engagement in the classroom. One mechanism that may explain how self-efficacious instructors foster engagement is autonomy-supportive practices. Undergraduate students’ perceptions of autonomy-supportive teaching were also positively related with classroom engagement. This finding corroborates a long tradition of research on autonomy-support and its benefits for classroom engagement (Jang, Reeve, & Deci, 2010). We extend the prior research on this topic by examining the perceived autonomy-supportive practices of GSIs as well as leveraging perceptions of undergraduate students rather than solely relying on teacher-reported data. One interesting result from our multilevel models was the cross-level interactions between instructors’ teaching self-efficacy and autonomy-supportive practices on undergraduates’ classroom engagement. The interaction effects suggested that when undergraduate students perceived moderate to high levels of autonomy-support, there were similar levels of undergraduate classroom engagement across levels of teacher self-efficacy. In other words, for more autonomy-supportive instructors, their undergraduate students are more engaged overall regardless of how self-efficacious their teachers are. Thus, our findings point to how instructors with low teaching self-efficacy who implement autonomy-supportive practices may have more engaged students. This result is promising given that new GSIs are often fearful and lack teaching self-efficacy; however, even with low confidence towards their teaching abilities, if they try to foster autonomy in the classroom, their students can still be engaged. Moreover, in some GSI teaching roles, there may be limited control for how much the GSI can change the instructional structure for the class, such as highly prescribed laboratory sections that must follow precise protocols in a short timeframe. In these cases, our findings suggested that high teaching self-efficacy among GSIs may serve as a buffering role when autonomy-supportive practices perceived by undergraduates were limited. One explanation for these findings may be that teaching self-efficacy and autonomy-support are compensatory, such that if one of these aspects is lacking in one’s teaching, then the other aspect compensates for this loss, in order to still support classroom engagement. This interaction pattern is more pronounced for STEM contexts than for non-STEM contexts, as indicated by significant three-way interaction effects. One possible explanation is that teaching self-efficacy has a greater compensatory effect when perceived autonomy support is low for classroom engagement in STEM disciplines because STEM contexts may be more vulnerable to low autonomy-support. STEM classes often consist of laboratory assignments with prescribed instructional approaches that dictate what undergraduate student should do step by step (termed “cookbook” labs). These kinds of classes have limited opportunities for undergraduate student autonomy. However, perhaps when the GSI has high teaching self-efficacy, they are still able to create engaging experiences for undergraduates in these situations. Once again, because gender was not accounted for in our analyses, caution must be exercised when interpreting STEM vs. non-STEM comparisons as they may be concealing gender effects. Although we found some evidence indicating that the relation between teaching self-efficacy and classroom engagement was moderated by perceptions of autonomy-support, our data did not support a mediational model. One explanation for this finding was how we operationalized perceptions of autonomy support from undergraduates’ perspectives, whereas prior studies measured autonomy-support as an instructor-report (Hascher & Hagenauer, 2016; Leroy et al., 2007). There is some research supporting a lack of congruence between teacher- and student-report measures of autonomy-support (Domen et al., 2019). Our data suggested teaching self-efficacy and student-perceived autonomy-support were relatively orthogonal; simply put, an instructor may feel efficacious about their teaching, but students may not necessarily be perceiving them as employing autonomy-supportive practices, or vice-versa. Moreover, because autonomy-supportive practices were theorized to be an indirect consequence of teaching self-efficacy (Woolfolk 101

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Hoy & Davis, 2005), perhaps there are other direct consequences mediating the relation between teaching self-efficacy and autonomy-supportive practices. Given the exploratory nature of the moderation and mediation models, we encourage future replications to investigate these complex relationships. Future research is also needed to further elucidate specific ways self-efficacious instructors foster classroom engagement. Perhaps as instructors are more engaged in their teaching, there is a contagion effect that bolsters students’ own engagement. Other factors discussed by Woolfolk Hoy and Davis (2005) such as instructor’s interest in the subject matter, openness to new teaching methods, or self-regulation of teaching behavior may be potential mediators between teaching self-efficacy and engagement to be explored in subsequent studies. 5.3. Limitations, future research, and conclusions It is important to note some limitations of our study. Although we controlled for a handful of demographic characteristics relevant to GSIs’ academic and pedagogical experiences, we lacked other demographic details such as gender and racial/ethnic identification. Increasing our sample size of GSIs as well as demographic details will allow for adequately powered analyses that further control for participant characteristics. For instance, the influence of GSI gender may contribute to differences between STEM and non-STEM disciplines. Moreover, the sample was recruited within only one U.S. university, which limited the results to the specific context of one institution. This context may influence the personal development of GSIs in ways that are not generalizable to other institutions. Furthermore, although the participants came from a variety of academic disciplines, STEM and non-STEM was the most parsimonious categorization. Nevertheless, our study was limited by not capturing every academic discipline and controlling for such variability in our models. This limits the generalizability of the study results and needs to be addressed in future research. Drawing from SCCT, we made connections in our findings to the sources of teaching self-efficacy, but we did not explicitly measure GSIs’ endorsement of the four theorized sources. Future research should combine psychological perceptions of such sources as well as reporting of representative educational experiences such as prior teaching experiences (Morris, Usher, & Chen, 2011). Additionally, antecedents (characteristics of instructors) and teaching self-efficacy measures were assessed at the same time point with the same self-reported approach. This could lead to an overestimation of relations through the same source bias and warrants caution when interpreting correlational data assessed at the same time point. Also, there are limitations with a self-reported measure of classroom engagement; future research could integrate observational and/or teacher-reported measures of engagement with student-reported instruments. Additional examination of the moderating role of autonomy-support is an important next step. In particular, a qualitative investigation of undergraduate students’ perceptions of instructor teaching self-efficacy and autonomy-support may illuminate dynamics of instructor motivation and student engagement. Another limitation in our methodology was the time gap in data collection when measuring graduate student teaching self-efficacy and their undergraduates’ perceptions. Because we needed to wait for undergraduates to experience instruction from their GSI, undergraduate student perceptions were surveyed mid-semester. However, this delay does not account for potential shifts in GSI teaching self-efficacy. Lastly, missing data could have been handled with multiple imputation techniques, which may have reduced bias in our analyses. To summarize, our results should be viewed as providing preliminary support for antecedents of teaching self-efficacy and the role of teaching self-efficacy on undergraduates’ classroom engagement. Teaching self-efficacy is multifaceted (Roche & Marsh, 2000); moreover, teaching self-efficacy is associated with classroom engagement, especially when undergraduates perceived low autonomysupport in STEM contexts. Altogether, these findings point to the importance of cultivating GSI teaching self-efficacy, while taking into account GSI characteristics and the classroom context. Appendix A Measure 1: Teaching Self-Efficacy Scale (adapted from DeChenne & Enochs, 2010) How confident am I in my ability to: Instructional Strategies 1 2 3 4 5

Spend the time necessary to plan my classes? Prepare the teaching materials I will use? Adequately grade my students’ exams and assignments Provide my students with detailed feedback about their academic progress? Evaluate accurately my students’ academic capabilities? Learning Environment

1 2 3 4 5 6

Think of my students as active learners, which is to say knowledge builders rather than information receivers? Promote a positive attitude towards learning in my students? Create a positive classroom climate for learning? Let students take initiative for their own learning? Promote my students’ confidence in themselves? Ensure that my students consider themselves capable of learning the material in my class?

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Measure 2: Teaching Assistant Demographic Questionnaire 1 How many semesters have you completed in your current graduate program? 2 How many semesters have you taught in a formal instructional role? (Being a K-12 teacher or TA is considered teaching experience, while tutoring or other informal teaching is not considered teaching experience for our purposes.) 3 Have you previously taken courses in pedagogy? Measure 3: Student Rating of Classroom Engagement 1 2 3 4 5

I I I I I

prepare for class meetings. actively participate in class. understand the material in class can apply what I learn to new situations. feel comfortable sharing my ideas in this class.

Measure 4: Student Rating of Perception of Autonomy Support 1 2 3 4 5 6

The The The The The The and 7 The

instructor is approachable. instructor motivates me to learn. way the instructor introduces new concepts supports my learning. way the instructor conducts this class keeps me engaged. feedback I am getting from the instructor is helping me learn. instructor balances following the lesson plan for our class with improvising to address students’ immediate needs, interests, questions. instructor creates a positive environment that promotes learning.

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