International Journal of Teaching and Learning in Higher Education 2016, Volume 28, Number 1, 75-93 http://www.isetl.org/ijtlhe/ ISSN 1812-9129 Investigating Postsecondary Self-Regulated Learning Instructional Practices: The Development of the Self-Regulated Learning Observation Protocol Leah D. Hoops and Shirley L. Yu Qianqian Wang Virginia L. Hollyer The Ohio State University Houston Independent School District University of Houston Promoting students’ self-regulated learning (SRL) is one way to improve postsecondary student success. However, few studies have investigated the instructional practices of postsecondary instructors that may support students’ SRL. This study sought to fill this gap. An undergraduate mathematics course was observed to determine instruction utilized in classrooms that could influence students’ SRL. Results showed that instructor references were made to four areas of SRL: (a) cognition; (b) motivation and affect; (c) behavior; and, (d) context. The majority of references concerned cognition and fewer messages addressed motivation. Findings are discussed in terms of postsecondary instructional practices that may foster students’ SRL. This project is significant because it developed an observation protocol to assess instructional practices that may support college students’ SRL in specific college courses: the Self-Regulated Learning Observation Protocol (SRLOP). As postsecondary outcomes have increasingly process (e.g., Boekaerts, 1996, 1999; Greene & Azevedo, become a national area of concern, a focus on 2007; Winne & Hadwin, 1998, 2008; Zimmerman, instructional practices in higher education has also 2000), Pintrich’s model was selected as a framework surfaced (Altbach, 2011). Failure rates in because it focuses on specific aspects of learning that undergraduate mathematics core courses, in particular, students can be taught to control. In particular, Pintrich’s have remained high (Gupta, Harris, Carrier, & Caron, SRL model includes context, a category exclusively 2006). For example, only 40 to 60% of students dedicated to students’ learning environment (i.e., one successfully pass college precalculus nationwide variable of particular interest in this study). Each of the (Olson, Cooper, & Lougheed, 2011). The high four areas of SRL will be described in more detail below attrition rates in college Science, Technology, including strategies instructors can use to foster students’ Engineering, and Mathematics (STEM) courses have SRL for their courses. prompted politicians and educators alike to focus on refining STEM pedagogy (McCray, DeHaan, & Cognition Schuck, 2003; Olson et al., 2011). One approach to increasing postsecondary success The first area of learning that students can regulate rates is by teaching students how to become more concerns techniques that students use to process effective self-regulated learners. Self-regulated learning information or perform a learning task, such as (SRL) is the proactive process through which students metacognitive strategies (Pintrich, 2000). There are become masters of their own learning and performance many types of cognitive strategies that have been taught (Pintrich, 2004). Self-regulated learners take initiative to college students through various methods such as in their education and persevere, constantly adapting to rehearsal, elaboration, and organization (Hofer, Yu, & their learning environments and tasks at hand Pintrich, 1998). Elaborative and organizational (Zimmerman, 2002). Becoming a more persistent self- strategies, such as concept mapping, have been shown regulated learner could especially benefit students in to result in deeper understanding of learned material historically challenging undergraduate STEM courses, (Hofer et al., 1998). It is well-established that cognitive such as mathematics. SRL is viewed as controllable and regulation is essential to deep and meaningful learning unstable (Pintrich, 2000, 2004); therefore, college (Winne & Hadwin, 1998). There are many ways that students’ SRL practices can be influenced by classroom instructors can promote students’ cognitive regulation. instructional practices. For example, teachers could encourage students to use specific strategies to learn or perform a task, prompt Theoretical Framework students to monitor their level of understanding or gauge students’ understanding themselves, or prepare For this project, we adopted Pintrich’s (2000; students to learn new information. 2004) model of SRL which proposes a framework for classifying four areas of learning that students can Motivation and Affect regulate: (a) cognition; (b) motivation and affect; (c) behavior; and, (d) context. Although there are currently In addition, motivation and affective components several other models of SRL that propose different play a key role in SRL (Pintrich, 1999, 2000; constructs and mechanisms involved in the learning Zimmerman & Schunk, 2007). Students can regulate Hoops et al. Self-Regulated Learning Observation Protocol 76 their motivation and affect just as they are able to contextual setting; therefore, students must utilize regulate and monitor their cognition (Pintrich, 2004; specific strategies to monitor, alter, and control Wolters, 1998, 2003). Motivation plays an especially their learning environments. Although students may important role in SRL because learners will not use self- be unable to control their instructors’ teaching regulatory strategies if they are unmotivated to do so styles or the content of their assignments, they can (Zimmerman, 2000). Moreover, measures of manage certain aspects of their learning achievement motivation have been shown to predict environment (Pintrich, 2004). The area of context is college students’ academic performance above other not completely “self”-regulated because much of aspects of students’ SRL and ability levels (Robbins, students’ learning tasks and environments are Lauver, Le, Davis, Langley, & Carlstrom, 2004). external and beyond their control; however, context Students’ interests (see Hidi & Renninger, 2006) as well is considered an area of SRL because students do as expectancies and values (see Eccles, 2009) are critical have some control over how their learning components of their achievement motivation. To foster environments are structured. In addition, academic students’ motivation in the classroom, college instructors content, such as instructor feedback and assessment could point out the usefulness of learning tasks so that tasks, serves as an agent in students’ SRL processes students are motivated to engage with course material. (Nicol & Macfarlane-Dick, 2006; Perry & Rahim, Moreover, students who feel that their instructors are 2011). Instructional scaffolding of learning tasks interesting are more likely to attend class (Gump, 2004); can help students regulate their cognition, therefore, instructors could focus on sparking their motivation and affect, and behavior. students’ situational interest by using humor. Postsecondary Self-Regulated Learning Behavior Because the majority of postsecondary learning Behavioral aspects of SRL reflect the effort that takes place outside of the classroom (Hofer et al., students put into learning tasks, including help-seeking 1998; Pintrich, 2004), college students must learn and time management (Pintrich, 2000). Students must to effectively regulate their own learning processes engage in activities to purposely activate, foster, and in order to perform well in their courses. Although sustain the learning process. Academic help-seeking, SRL skills are critical to postsecondary success can be advantageous in improving students’ (Hofer et al., 1998), many college students are not understanding and achievement (Pintrich, 2000). Help- effective self-regulated learners (Bembenutty, seeking behaviors include utilizing the various learning 2008). Students often rely on the external support resources and supports on campus, such as learning of their teachers through secondary schooling to centers and course review sessions. Time management direct their learning processes and find managing behaviors, such as creating study schedules, help direct collegial coursework to be challenging (Boeakarts, the learning process and are typically emphasized in 1999). Moreover, introductory undergraduate SRL interventions (Hofer et al., 1998; Pintrich, 2000, courses, such as mathematics, are often taught in 2004). Effective self-regulated learners actively engage large lecture halls (McCray et al., 2003; Olson et in behaviors, such as help-seeking and time al., 2011) where instructors are unable to provide management, that help students reach their academic students with the individualized feedback and goals. Postsecondary instructors can encourage students scaffolding that learners received through to engage in these types of behaviors outside of the secondary education. In large lecture courses where classroom or promote positive behavioral regulation instructors rarely are able to interact directly with during normal instruction. For example, an instructor their students, learners bear an even larger could suggest that students visit the campus tutoring responsibility in monitoring and controlling how center to receive help on challenging assignments or much they learn. As noted by Meyer and Turner scaffold students’ use of time on in-class learning tasks. (2002, p. 19), “co-regulation between a teacher and twenty-some students with varying needs and competencies is highly complex in whole-class Context instruction.” If co-regulation is complex in a classroom of twenty-some students, imagine how Finally, the contextual or environmental area of complicated it can be in a large undergraduate SRL involves external aspects specific to the lecture hall containing hundreds of students. learning task, such as classroom settings or rules of Therefore, it is of particular importance that an assignment (Greene & Azevedo, 2007; Lodewyk, students be taught to effectively self-regulate their Winne, & Jamieson-Noel, 2009; Pintrich, 2000, own learning in large courses in order to 2004; Zimmerman, 1989). All learning occurs in a successfully master the complex material. Hoops et al. Self-Regulated Learning Observation Protocol 77 Literature Review qualitative methods are well-suited to explore the relationship between teaching and learning during Postsecondary Self-Regulated Learning Instruction instruction (Meyer & Turner, 2002). Additionally, because SRL is a multi-dimensional construct (Perry & Student success courses. Many formal instructional Rahim, 2011; Winne, 2011), qualitative methods, such interventions, such as Student Success Courses, have been as classroom observation, are suitable ways to explore designed to help college students become better self- SRL within educational environments. Studies regulated learners (Wolters & Hoops, 2015. Student examining teachers’ instructional practices that support Success Courses (SSCs) teach students theory and strategies students’ SRL have mostly been conducted exclusively of SRL to help students achieve academic success. These in K-12 classroom settings. courses have proven successful in increasing students’ SRL Scaffolding elementary self-regulated learning behaviors (e.g., Forster, Swallow, Fodor, & Foulser, 1999; in math class. Meyer and Turner (2002) have utilized Hofer & Yu, 2003; Hoops, Yu, Burridge, & Wolters, 2015; qualitative methods to investigate instructors’ Petrie & Helmcamp, 1998), grades (e.g., Bail, Zhang, & scaffolding of elementary students’ self-regulation Tachiyama, 2008; Tuckman, 2003; Tuckman & Kennedy, development. The researchers utilized discourse 2011; Weinstein, 1994), retention (e.g., Forster et al., 1999; analysis to record and code classroom observation data Lipsky & Ender, 1990; Tuckman & Kennedy, 2011), and of teacher-student interactions during whole-class math graduation rates (e.g., Bail et al., 2008; Schnell, Louis, & lessons. Teachers’ scaffolding comments were coded Doetkott, 2003; Tuckman & Kennedy, 2011; Weinstein, under three categories: (a) student understanding; (b) Dierking, Husman, Roska, & Powdrill, 1998). autonomy; and (c) positive classroom climate. Non- Integrated approach to strategy instruction. The scaffolded responses were coded as either teacher- SRL strategies taught in SSCs can also be integrated controlled or nonsupportive motivational or into traditional academic course curriculum (Hofer et socioemotional. Finally, code proportions were al., 1998; Weinstein, Acee, & Jung, 2011); an calculated for each classroom by lesson and total integrated approach to SRL instruction can help instruction time observed. Discourse patterns were students thrive in demanding college courses by compared to understand how instructors could scaffold providing learners with the tools to self-regulate their students’ self-regulation during normal classroom study habits for a particular course. Embedding strategy instruction. instruction into normal course curriculum increases the Promoting students’ self-regulated learning likelihood that students will apply the strategies they through classroom structure. Perry and colleagues have learned to the material they are currently learning have also made advancements in investigating (Hofer et al., 1998). Additionally, the integrated contextual aspects that support SRL development in approach to SRL instruction can be particularly helpful the classroom through qualitative methods. Much of to less-proficient self-regulated learners (Barrie, 2007; Perry’s work has sought to understand how Cornford, 2002; Weinstein, Tomberlin, Julie, & Kim, classroom features promote or constrain children’s 2004). Therefore, investigating instructors’ natural SRL development and engagement in a variety of integrated approaches to SRL instruction could help classroom environments (Perry & Rahim, 2011). researchers understand how and if current Through observation and interviewing, her work has postsecondary classroom climates are conducive to focused on teachers’ speech and behaviors that fostering students’ SRL behaviors. promote SRL and how students respond to such promptings. During classroom observations, an Observing Self-Regulated Learning Instructional instrument was used to collect three types of Practices information: (a) classroom; (b) teacher and students’ speech; and, (c) high or low SRL environment Although self-reports are the primary tools used to (Perry, 1998; Perry, Hutchinson, & Thaurberger, measure SRL (Perry & Rahim, 2011), it has long been 2007; Perry & VandeKamp, 2000; Perry, argued that self-report data alone are insufficient for VandeKamp, Mercer, & Norby, 2002). Collecting the understanding the complexities of SRL in real contexts second type of information, teacher and students’ such as classrooms (Perry & Rahim, 2011; Perry & speech, involved recording a running record of what Winne, 2006; Winne, Jamieson-Noel, & Muis, 2002; occurred in the classroom. This often included Winne & Perry, 2000). According to Meyer and Turner teacher and student verbatim responses (Perry, (2002), researchers must study the contexts in which 1998). During observation, observers recorded the students’ SRL develops in order to better understand times that student-teacher and student-student events self-regulatory processes in general. Because SRL took place. Based on running record observations, supports and is supported by social forms of learning, classrooms were designated as either high or low such as within a classroom (Perry & Rahim, 2011), SRL-supportive (Perry, 1998). Hoops et al. Self-Regulated Learning Observation Protocol 78 Findings from this body of research have revealed extant integrated teaching practices through that autonomy-supportive, structured classrooms that observation. In this manner, we sought to discover offer meaningful learning tasks for students to master which instructional practices, if any, were already in over multiple sessions best promote children’s’ SRL place that might influence students’ SRL in courses engagement (Perry & Rahim, 2011). Specifically, with historically low success rates. To accomplish this elementary children were able to identify effective task, the following research question was posed: What strategies students could use – or that they had used types of instructional practices are utilized in a college themselves – for self-regulating their writing (Perry & precalculus classroom that could influence students’ VandeKamp, 2000). Most students (78%) mentioned self-regulated learning for the course? help-seeking strategies, such as seeking help from their teacher, parent, or peer if students were experiencing Method difficulties with a writing project. Additionally, 30% of students mentioned using strategies to persist in the face Participants of difficulty, such as paying attention to the teacher or “try very, very hard” (Perry & VandeKamp, 2000, p. Participants were a university mathematics 839). Therefore, in elementary classrooms where instructor, students enrolled in two sections of her instructors were observed explicitly promoting SRL undergraduate precalculus course (N = 645), and eight practices, elementary children reported greater peer tutors at a large southeastern public research knowledge of and engagement in SRL. university. The observed instructor (who will be Investigating classroom motivational climates. referred to as “Ms. Math” for the remainder of the Additionally, a line of research investigating the impact article) was a female lecturer in the mathematics of instructional practices on classroom motivational department who also taught courses for the natural climates has been conducted utilizing the Observing sciences and mathematics teacher certification program Patterns of Adaptive Learning (OPAL; Patrick et al., at the university. Ms. Math had taught at the university 1997) protocol for classroom observations (e.g., for 10 years at the time of data collection; her Morrone, Harkness, D’Ambrosio, & Caulfield, 2004; instructional practices have been institutionally Patrick, Anderman, Ryan, Edelin, & Midgley, 2001; recognized by a university teaching excellence award. Patrick & Ryan, 2008). The OPAL was designed Although demographic data were not collected for the “around narrative running records of teacher and student participants, the university where the sample student behavior observed during classroom was taken is diverse with no ethnic majority. In 2012, instruction” (Patrick et al., 1997, p. 1). Researchers university students reported their ethnicities as follows: utilizing the OPAL recorded and coded observational African American (11%), Asian American (19%), data based on categories grounded in achievement goal Caucasian (32%), Hispanic (25%), International (9%), theory (Patrick et al., 1997). Although this body of Multiracial (3%), and Other (1%). In addition, the research was not focused on SRL instructional practices reported mean age of undergraduate students was 22.5 specifically, utilizing a running record observational years. approach guided by a specific theoretical framework is an appropriate method for evaluating SRL practices Observational Protocol and Data Collection within a classroom context. The Self-Regulated Learning Observation Protocol Purpose of Study (SRLOP) was developed by the research team to investigate instructional practices in college classrooms Although past research efforts have made great that can support students’ SRL for a particular course. strides in investigating SRL-supportive instructional Specifically, the SRLOP was designed to utilize in the practices in K-12 classrooms, a critical need exists for undergraduate mathematics course studied. Although studies that seek to understand contextual aspects of designing an observation protocol was not an original postsecondary classrooms that support students’ SRL study objective, the instrument was created in order to development. The purpose of this study was to answer our specific research question. Therefore, the investigate postsecondary instructional practices that framework that emerged is both a product and measure may support students’ SRL in an undergraduate of this research project. The SRLOP is based on mathematics course, specifically, precalculus. Pintrich’s (2000, 2004) model of SRL and includes Understanding these instructional strategies can help multiple categories of instructional practices that can educators identify pedagogies that contribute to student influence students’ SRL. The SRLOP coding structure success in traditionally demanding college courses. categorizes observed teacher and students’ behaviors This study contributes to research on SRL instruction in and statements according to the four areas of learning postsecondary education by examining an instructor’s that students can control (i.e., the four aspects of SRL): Hoops et al. Self-Regulated Learning Observation Protocol 79 (a) cognition; (b) motivation and affect; (c) behavior; (“poppers”) during most class sessions which students and, (d) context. A description of the final SRLOP were asked to turn in at the end of class for a grade; if coding categories within these four areas will be students needed help solving popper questions, they would presented with the results as they emerged and were raise their hands to solicit a tutor’s help. Students could refined throughout this research project. also raise their hands to receive help from tutors during The OPAL development process outlined by Ms. Math’s lectures. This in-class intervention was meant Patrick and colleagues (1997) strongly guided this to provide more individualized help to students than is project’s observation process and the creation of the typically possible in large lecture courses. SRLOP. The protocol is both a product of a priori At the beginning of the spring 2012 semester, the theory (i.e., Pintrich, 2000, 2004) and a grounded research team met to discuss the fall 2011 data and the theory approach. During the first class of the fall 2011 themes that emerged from it. A final coding scheme semester, the first author observed one class of one was then developed based on the fall data and Pintrich’s section of Ms. Math’s precalculus course with (2000, 2004) SRL framework that would be used to instructor consent. Enrollment in this course was 500 code the existing data and to guide future observations. students, and it was taught in a large lecture hall; In this manner, the categories within each of the four therefore, the researcher was able to observe areas of SRL emerged from the data using the constant- unobtrusively by sitting in the back of the room. During comparison method utilized by grounded theory the first class, the researcher recorded narrative running researchers; that is, we searched for “themes and records of what occurred in the classroom, paying patterns to build theory” (Glesne, 2011, p. 187) using particular attention to comments the instructor made constant case comparison. regarding students’ SRL practices in the four areas of The decision was then made to observe an learning which were relevant to research interests. This additional unit of Ms. Math’s precalculus course to (a) observer made note of time throughout observation, test and finalize the protocol, and (b) collect a reliable documenting events in sequential order. This type of dataset to answer this project’s original research observational strategy is aligned with the method used question. The precalculus section observed during by Perry and colleagues (Perry, 1998; Perry & spring 2012 was much smaller than the previous section VandeKamp, 2000; Perry et al., 2007; Perry et al., (i.e., less than 200 students). Because the in-class 2002); we chose this approach to get a sense of what tutoring intervention was introduced partway through naturally occurred in the classroom and how, or if, Ms. the semester as it was during the fall, a unit near the end Math promoted students’ SRL during class time. of the semester was selected for data collection to gain The first author observed an additional class session insight into what happens during regular instruction during the second week of the semester to set the time (i.e., at a time in the semester when both students, standard for data collection and to gain a fuller sense of tutors, and instructor had settled into their “normal Ms. Math’s instructional behaviors. After the second course routine”). Over the course of five weeks, the observation was complete, a second observer (third first and third authors alternated turns observing two author) with university teaching experience was trained consecutive class periods using the new protocol. This on the observational protocol by the first author. All rotation schedule was designed so that each observer subsequent observations were conducted by the second was able to observe sequential lessons in order to gain a observer for the duration of the semester. Because the better understanding of how the instructor stopped and observed course met twice a week, the second observer started each lesson. A total of 11 hours of observation typically attended and collected data during both of the data (nine periods) were collected during the spring weekly class sessions. Over the duration of the fall 2012 semester. After spring 2012 data collection was semester, a total of 22 periods (33 hours) of classroom complete, the first and second author met to revisit the activity were observed and recorded. protocol and confirm the SRLOP categories before During the third week of the semester, the presence proceeding with data analysis. of in-class peer tutors became a part of normal course procedures. Peer tutors were student staff at the Analysis of the Data university mathematics department’s tutoring center. The tutoring intervention was implemented as part of an Once initial SRLOP categories were finalized, the institutional and departmental effort to improve student first and second author independently analyzed the success rates in STEM courses. Moreover, Ms. Math same class period of spring data (over 10% of the total actively worked to incorporate student success observed spring unit) using NVivo 9 qualitative initiatives, such as the peer tutoring program, into her analysis software. The coders (i.e., first and second classrooms. Tutors typically arrived to class 10 minutes authors) were guided by a list of coding categories and into each class and positioned themselves around the descriptions designed collaboratively by the research lecture hall. Ms. Math gave in-class pop quizzes team. Interrater reliability (% agreement) of coding Hoops et al. Self-Regulated Learning Observation Protocol 80 decisions was then calculated for the double-coded have been edited to improve readability and preserve data. Percentage agreement was chosen over kappa confidentiality of study participants. because the researchers developed the coding categories together. Therefore, it was deemed unnecessary to take Observed Cognition chance of agreement into consideration since researchers should achieve agreement intentionally. The 169 cognitive references made by the instructor After reaching consensus on all codes, the first author during the observed spring 2012 unit divided into four continued to analyze the remaining eight class periods main categories as follows: Metacognition (40%), Test- of data independently. Taking Strategies (29%), Information Processing Initial calculation of interrater reliability yielded Strategies (23%), and Advance Organizers (8%). high agreement (≥ 90%) agreement on the majority of Metacognition (n = 68). References to students’ coding categories (i.e., the most micro-level data under metacognition included the instructor prompting which data were able to be coded). To reach consensus, students to engage in metacognitive processes, such as the coders discussed categories with lower agreement, thinking about how to solve a problem or engage in a revisiting the analyzed data together until 100% learning task. Metacognitive statements help students agreement was achieved. During the final coding think about their cognitive processes and/or trigger process, additional coding classifications emerged them to do so. Of the 68 references made regarding further refining the SRLOP framework. Many of these Metacognition, 72% involved the instructor checking new classifications resolved ambiguities in the original for students’ understanding of lecture material and 28% categories that led to low interrater reliability, helping involved her prompting students to think about how to to confirm the final observational framework and codes. solve a problem or engage with course content. Finally, the first and fourth authors met to complete a member check of final coding decisions. The fourth Example 1: author (“Ms. Math”) was selected for member check to "Anyone have questions about how I promote higher internal reliability of the coded data manipulate the negative sign?" (Glesne, 2011). Example 2: "There are two answers to the question. Results However, let me ask you a question. What if the measure of the angle is 15, not 30?" A total of 405 statements or “chunks” of spring 2012 observation data were coded under the SRLOP Test-Taking Strategies (n = 49). This category framework. Of the four main SRL categories, the contained instances when Ms. Math mentioned specific observed instructional practices of the mathematics strategies or resources that students could use while taking professor during the final observed unit focused mostly an assessment. It should be noted that all exams for this on Cognition (42%), Behavior (29%), and Context course were administered online via the department’s (23%), with only 6% of all observed instruction computer lab testing center. Test-taking strategies concerning student Motivation and Affect. The final included ways in which students should have used SRLOP included 12 major categories of SRL resources, such as sanctioned formula sheets, as well as postsecondary instructional practices within the four cautions against poor test-taking strategies (i.e., specific areas of SRL (Cognition, n = 4; Motivation and Affect, things students should avoid doing while taking an n = 2; Behavior, n = 2; Context, n = 4). assessment). The majority of the 49 references to Test- Table 1 displays the percentages of all SRL references Taking Strategies concerned a formula link that students made during the spring observation period arranged by would need to utilize during the upcoming exam. SRLOP category. Appendix A includes a complete list of Although the formulas were available to students via the the final SRLOP categories including descriptions and link, Ms. Math made sure that students understood exactly examples of instructional references. SRLOP categories how they should use the link during test-taking. and subcategories are arranged first by area of SRL, then in alphabetical order. Appendix A serves as the final Example 1: SRLOP framework and can be utilized by future Ms. Math emphasizes the importance of researchers to observe postsecondary classrooms. All the formula sheet and gives students references in Appendix A are from the fall 2011 instructions for using it during the next observation data that helped shape the protocol’s exam. framework. Instructional strategy results will be presented Example 2: first by SRLOP categorization. Each category will be "Here is the formula sheet. Get to know it described and two examples will be given. Examples well...Here is the formula sheet that will provided are from the spring 2012 observation period and be on the link." Hoops et al. Self-Regulated Learning Observation Protocol 81 Table 1 Instructional References to Self-Regulated Learning Arranged by SRLOP Categories References N % SELF-REGULATED LEARNING TOTAL 405 100 Cognition 169 42 Metacognition 68 40 Test-Taking Strategies 49 29 Information Processing Strategies 39 23 Advance Organizers 13 8 Motivation and Affect 26 6 Value 18 69 Interest 8 31 Behavior 118 29 Help-Seeking 102 86 Time Management 16 14 Context 92 23 Student Responsibility 71 77 Task Difficulty 10 11 Instructor Feedback 7 8 Rules and Management 4 4 Note. Table 1 only reflects data collected during the spring 2012 semester. All percentages displayed represent each category’s percentage of the largest category to which they belong. For example, the Cognition category represents 42% the total SRL references (N = 405); Metacognition represents 40% of the Cognition category (n = 169). Therefore, the total number of references displayed in the N column exceeds 405, the total number of SRL references. Information Processing Strategies (n = 39). This Organizers, alerted students to what content would be category included instances Ms. Math mentioned a specific covered in class that day. This area includes any time the strategy that students could use to process information instructor set the tone of the day's lecture by letting students and/or taught students a strategy to help them learn the know what content would be covered or prepared them to course material. These types of statements provide students recognize and process the new material. These statements with tools to process, understand, or display information. were usually made at the beginning of class. The 39 Information Processing Strategies alerted students to problem-solving “tricks” such as using substitution as a tool. Example 1: "Let us get started now. Here we go. We Example 1: are going to study algebra with identity." Ms. Math starts to work out the next Example 2: example and explains to students a "Today we are going to start test 4 strategy they can use to solve the materials." equation. Example 2: Observed Motivation and Affect Ms. Math tells students the name of the strategy she is using to solve this equation The instructor utilized fewer instructional practices (using the conjugate forms). concerning aspects of students’ achievement motivation (n = 26) relative to the other three areas of SRL. Advance Organizers (n = 13). The least-utilized Motivational references fell into two basic categories as cognitive reference made by the instructor, Advance follows: Value (69%) and Interest (31%). Hoops et al. Self-Regulated Learning Observation Protocol 82 Value (n = 18). This motivational category engaging in help-seeking activities during class, and included instances when the instructor highlighted the only 2% referred students to resources where they could importance or usefulness of a task. These statements get help outside of the classroom. Also, most in-class helped students know what their focus should be and help-seeking involved peer assistance rather than how to better regulate their study time based on the students seeking help from Ms. Math. significance of mastering certain tasks (i.e., spend more time studying concepts and tasks that will be well- Example 1: represented on an exam or relevant to a future career). Ms. Math enters the classroom and begins Ms. Math’s statement regarding value were usually to set up. She talks to a few students as explicit (i.e., specific) and not simply ones in which she sets up who have questions. students had to infer the importance of the task. These Example 2: statements often included the word “important”, Students communicate with each other to transparently alerting students to the material critical to work out the problem. comprehend. Time management (n = 16). The second behavioral Example 1: category included instances where the instructor made Ms. Math works out a problem and says, statements or suggestions regarding students’ use of time to "This is important from an identity prepare for the course outside the classroom. Of the 16 Time standpoint." Management promptings, 56% reminded students of course Example 2: deadlines and 44% offered guidance for managing time "Here is another one. This one is for spent on learning tasks. Ms. Math reminded students of engineering, math, and science majors." course deadlines as well as institutional deadlines that impacted the course, such as add/drop dates. Time Interest (n = 8). In the Interest category, the Management statements only comprised 4% of the total instructor triggered students’ situational interest by SRL references made by the instructor. making humorous remarks. This includes instances where the instructor gained students’ attention by Example 1: saying something funny, sharing a personal story, or Ms. Math announces that homework is making other types of remarks meant to spark or due Saturday, and homework is due today maintain situational interest. from Tuesday’s lecture. Example 2: Example 1: “Some of you may be saying, ‘Oh my "How many times is that now that I have God, she’s going so fast!’ Yes, I am! I’m mentioned the link? If any of you forget trying to speed you up so you don’t take this, I will personally execute you!” The 30 minutes on the problems and then students laugh. don’t have time for the free response Example 2: questions when you take the exam.” Ms. Math tells students that now is the time to ask questions because she won’t Observed Context be with them on the exam. She says that Finally, the 92 contextual references made during the come exam time, she will be having observed spring 2012 unit fell into four categories as cappuccino and knitting, and it would be follows: Student Responsibility (77%), Task Difficulty really amazing if she could do that while (11%), Instructor Feedback (8%), and Rules and giving them a review. Management (4%). Student responsibility (n = 71). This category Observed Behavior included Ms. Math’s statements regarding students’ responsibility on evaluative tasks, such as exams, The 118 behavioral references divided into the two homework assignments, quizzes, and class discussion. Ms. main behavior categories as follows: Help-Seeking Math frequently referenced students’ responsibility in her (86%) and Time Management (14%). class, and these comments comprised 18% of the total Help-seeking (n = 102). This behavioral category SRL references made during the academic unit. The 71 included instances where students sought help during Student Responsibility statements pointed out material class by asking questions and statements Ms. Math students were specifically responsible for mastering, such made to address the giving or receiving of help. The as material to be covered on assignments and exams and majority of Help-Seeking references (98%) encouraged actions students must take (e.g., memorize a formula or students to find assistance or involved students create a formula sheet). Hoops et al. Self-Regulated Learning Observation Protocol 83 Example 1: Example 1: “Be prepared for this question because it One student asks a question, and the Ms. is a quiz question.” Math cannot hear her. "Guys, I cannot Example 2: even hear her. Could you please talk “You must have this memorized by heart." less?" Example 2: Task difficulty (n = 10). This contextual category “Does everybody have the reservation for included instances where the instructor highlighted the test 4? Make sure you have the difficulty level of a learning task. These statements reservation for test 4.” helped students properly evaluate the difficulty level of a task and suggest the level of effort required to Discussion complete the task, providing guidance for study time and effort regulation. Task Difficulty statements were The purpose of this study was to investigate surprisingly scarce considering the perceived difficulty postsecondary instructional practices that support level of the subject. students’ SRL in an undergraduate mathematics course, specifically, precalculus. Through observations of an Example 1: undergraduate mathematics course taught in a large “Whenever you see double angles, get lecture format, we created an observational protocol happy because they’re not real hard.” and then utilized it to code the instructional practices of Example 2: the observed instructor. This observational protocol “This is a really complicated one.” differs from extant instruments in that it classifies observed instructional practices by four areas of SRL. Instructor feedback (n = 7). This category We also did not seek to count SRL-instructional included the instructor’s comments that provided practices by category as they were observed. feedback regarding students’ performance and Additionally, the SRLOP is not meant to classify behavior. For example, Ms. Math would reinforce the observed classrooms as either high or low SRL asking of questions or discusses performance on past supportive, but was designed as a tool to better assignments. Instructor Feedback is categorized under understand current instructional practices that may context because it is an aspect of the learning support college students’ SRL. We are not making environment that can impact students’ regulation of claims that Ms. Math’s observed practices did, in fact, cognition, motivation/affect, and behavior. Instructor promote her students to engage in SRL practices for her Feedback was utilized rarely compared to other course; we simply assert that the practices we observed contextual promptings, but the seven comments made could trigger – or guide – students to regulate their own by the instructor praised students for participating in learning. class. Regarding observed SRL-instructional practices, we found that through various practices and statements, the Example 1: precalculus instructor, Ms. Math, focused equally on the "Those are good questions. They are areas of behavior and context and spent the majority of her great!" instruction time prompting cognitive aspects of student Example 2: learning. However, very few references were made to Ms. Math makes a small mistake, and motivational and affective features of education relative to students correct it. She thanks students, other areas of learning that students can control. We will makes the correction, and then moves on. discuss the implications of these findings, organized by Pintrich’s (2000, 2004) areas of SRL. Rules and management (n = 4). The last SRLOP category included Ms. Math’s mentioning explicit and Cognition Language implicit behavioral guidelines, norms, and expectations for the classroom, as well as the procedures by which Findings revealed that metacognitive promptings the classroom functioned. Rules and Management represented 17% of the total SRL references made by references included covering the class rules on the Ms. Math during the observed academic unit. syllabus along with statements reflecting course Metacognition is a very important aspect of students’ policies, such as the usage of cell phones in class. Rules SRL (Winne & Hadwin, 1998; Zimmerman, 1989). and Management were mainly referenced when the These types of learning strategies are useful and help instructor asked students not to talk or reminded them students learn new information effectively (McCray et to make their reservations to take the upcoming exam at al., 2003). One plausible explanation for the instructor’s the computer lab testing center. heavy emphasis on cognition could be the high salience Hoops et al. Self-Regulated Learning Observation Protocol 84 of cognitive strategies in achieving success in a need help and then elicit help from reliable sources mathematics course. This finding alone could begin to whenever necessary. One quarter of Ms. Math’s SRL tell us more about mathematics instruction. Although it instructional practices involved help-seeking; this cannot be determined how Ms. Math’s promptings finding should be interpreted in light of the unique impacted her students’ SRL, our observers were able to situation of the in-class tutoring intervention. recognize Ms. Math’s emphasis on this aspect of Although help-seeking was a large part of the cognition in the observed class sessions. specific course and unit examined, we realize that this is typically not the case in large undergraduate Motivation and Affect Language courses. However, the collaborative learning environment that the weekly pop-quizzes (“poppers”) Although cognitive strategies are undoubtedly and support of in-class tutors and classmates created essential to students’ SRL in mathematics courses, might serve as an example of best-practices. motivation also plays a critical role in SRL (Pintrich, Past research has shown that problem-based 2000; Zimmerman & Schunk, 2007), including environments, where tasks are structured to promote impacting the types of strategies students choose to use student engagement with course material during class (Pintrich, 1999) and how much effort they expend sessions, are conducive to student learning and success (Schunk & Pajares, 2009; Schunk, Pintrich, & Meece, in undergraduate mathematics courses (Olsen et al., 2008). Cognitive and affective aspects of the classroom 2011). Because active problem-solving during class can environment have been found to be interrelated; promote student learning and collaboration, perhaps in- students utilize more productive learning strategies class interventions such as the one we observed would when instructors employ motivational instructional aid in promoting students’ adaptive help-seeking practices (Turner et al., 2002). Therefore, the finding behaviors (Ryan, Patrick, & Shim, 2005; Ryan & that little instructional time was spent fostering Pintrich, 1997; Ryan, Pintrich, & Midgley, 2001) in students’ motivation to learn in the precalculus course other challenging undergraduate courses. suggests an opportunity to enhance Ms. Math’s Additionally, we found that only four percent of pedagogy. At the end of our study, Ms. Math was total SRL instructional references in a complete trained to integrate more motivational strategies into academic unit were made regarding time management. her normal course instruction. The ended result is that Perhaps, the lower number of references could be her future students’ SRL could improve, ultimately attributed to the point in the semester when resulting in better success rates in Ms. Math’s more observations were taken. Postsecondary instructors challenging courses. typically discuss course deadlines at the beginning of We would also like to point out that although the semester when the syllabus is covered. Therefore, Ms. Math made fewer motivational references the observed lack of focus on students’ time compared to other areas of SRL, it is noteworthy that management could represent postsecondary instructors’ she did utilize some motivational strategies as part of tendency to focus heavily on time management at the her normal instructional practices. To give some start of the semester only, leaving students with background, our research project developed out of a guidance to manage their time for the duration of the shared interest and collaborative effort to improve semester. Because effective time management skills student success in STEM by the mathematics contribute to students’ success in college (Britton & instructor (fourth author) and the second author. The Tesser, 1991; Pintrich, 2004), it could be useful for instructor’s concern for student achievement could instructors to provide students with more temporal explain the class time she spent fostering student guidance throughout the semester, particularly in motivation. Ms. Math’s use of task and utility value challenging courses such as precalculus. references, specifically, is encouraging. Learners are more likely to put forth higher amounts of effort on Context Language learning tasks they find personally relevant and valuable (Cole, Bergin, & Whittaker, 2008). We Almost 25% of Ms. Math’s referenced instructional believe that encouraging more STEM instructors to practices concerned contextual aspects of SRL. Ms. focus on promoting student motivation could Math might have focused heavily on contextual aspects possibly improve students’ SRL and academic of learning tasks due to the challenging nature of tasks achievement in historically challenging courses. (e.g., assignments, exams, and studying) involved in her course. Particularly noteworthy is our finding that 18% Behavior Language of the instructor’s total SRL references made during the observed spring unit concerned students’ responsibility According to Pintrich (2004), effective self- in the course. SRL is the proactive process through regulated learners actively monitor whether or not they which students become masters of their own learning