Metacognition instruction enhances equity in effective study strategies across demographic groups in the general chemistry I course

Abstract

Explicit teaching of metacognition, ‘thinking about one's thinking,’ has been shown to improve achievement scores in the general chemistry tests and facilitate the awareness and adoption of metacognitive strategies. However, very few studies have investigated variations in the reported metacognitive strategies employed by college science majors by gender, race/ethnicity, and first-generation status. Additionally, little is known as to whether metacognition instruction makes any difference in closing the reported existing equity gap in the use of effective study strategies across demographic groups. Using a qualitative approach and open-ended questionnaires completed by 259 general chemistry 1 students, we investigated variations in reported (1) study strategies including metacognitive strategies between demographic groups in the general chemistry I course prior to and immediately after a 50 minute metacognition lesson retrospectively, (2) long-term gains in the study strategies and the adoption across the demographic groups over a semester after the metacognition instruction, and (3) transfer of the reported acquired study strategies to other science courses beyond the general chemistry lecture course. The findings showed evidence of equity gaps in the reported use, gains, or adoption of specific study strategies related to lower-order study strategies (LOSSs) and higher-order study strategies (HOSSs) based on gender, race/ethnicity, and first-generation status prior to and after the metacognition instruction. However, the identified equity gaps in LOSSs and HOSSs prior to the metacognition instruction were narrowed or closed with students’ exposure to the study strategies. Additionally, the findings indicated that over half of the study participants from all the demographic groups, except males and first-generation participants reported transfer of the acquired study strategies from the metacognition instruction to other courses. These findings imply the existence of equity gaps in study strategies across demographic groups in general chemistry I. Additionally, explicit teaching of study strategies, including metacognition, can relinquish the existing equity gaps.

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Introduction

The percentage of underrepresented minority groups in the United States of America (USA), such as women, minority ethnic groups (Black/African American, American Indians or Alaska Native, Pacific Island, Hispanics) in college science, technology, engineering, and mathematics (STEM) programs is significantly increasing; however, the attrition rates of underrepresented groups remain a national concern in the USA (Hurtado et al., 2010; Chen, 2013; Bressoud, 2020; Fry et al., 2021). Consequently, this significantly impedes the innovative capacity of the nation's science and engineering enterprise, leads to inequitable participation of talented populations in driving the economy (National Academy of Sciences, 2007; NSF, 2021), and negatively affects local, national, and global demand for highly skilled STEM workers (NSF, 2021). Poor grades in the introductory STEM courses that serve as prerequisites for STEM programs are among the known factors for attrition in STEM (Seymour and Hewitt, 1997). Specifically, students in general chemistry, a sequence course and pre-requisite for many STEM programs, must excel with the minimum required letter grade of a C in the course to pursue their declared STEM major. However, many students find general chemistry difficult (Cousins, 2007) and a major barrier to pursuing their STEM majors, especially the underrepresented minority student groups (Barr et al., 2008; Harris et al., 2020). As such, interventions are urgently needed to level the playing field for all students toward equitable learning outcomes.

The widespread adoption of student-centered approaches has shown promising results in narrowing the opportunity gap between marginalized and non-marginalized students (Freeman et al., 2014; Harris et al., 2020; Theobald et al., 2020). For instance, a meta-analysis study reported by Harris et al. with records obtained from 25 768 introductory general chemistry students revealed that the opportunity gap based on gender, race/ethnicity, socioeconomic status, and family education level ranged from 0.12 to 0.54 on a 4-point scale (Harris et al., 2020). The authors also found that underrepresented groups were more likely to drop out if they performed below a C-than well-represented groups, when controlling for academic preparation, but were more likely to persist if they attained at least a C grade (Harris et al., 2020).

Despite many efforts to engage students with the learning material, it is imperative to acknowledge that many first-year college students struggle not because they lack the capability, but because they are unaware of effective study skills (King, 1992; Roediger III and Karpicke, 2006; Kornell and Bjork, 2008; Yan et al., 2016; McCabe, 2018; Mutambuki et al., 2020; Muteti et al., 2021). Numerous studies have reported the overuse of rote memorization over higher-order thinking skills and effective study strategies in introductory STEM courses, including general chemistry I (Taraban et al., 1999; Karpicke et al., 2009; Cook et al., 2013; Zhao et al., 2014; Muteti et al., 2021). For instance, Karpicke et al.'s study with introductory STEM undergraduates in a controlled cognitive science laboratory in which the participants ranked the study strategies they employed in learning indicated that reading and rereading was the top-ranked followed by practicing problems, use of flashcards, rewriting notes, small-group learning, cramming, among others. Interestingly, 58% of the participants rarely employed self-regulation skills, such as self-testing (Karpicke et al., 2009).

Mutambuki et al. found metacognition instruction and active learning combination significantly boosted the performance of general chemistry students on cognitively demanding concepts assessed in the general chemistry I tests compared to active learning alone. This authors’ finding suggests that metacognitive awareness infused with student-centered learning approaches is effective. Muteti et al. (2021) also found that general chemistry I students reported the overuse of rote memorization strategies and poor study habits, but little use of metacognitive strategies, particularly regulation strategies. However, metacognition instruction increased the participants’ awareness and adoption of effective higher order-thinking strategies, including metacognitive knowledge and regulation strategies, with 67% of the participants reporting a positive influence of the metacognition instruction in the course (Muteti et al., 2021). Buy-in in metacognitive strategies was also associated with 7% lower DF letter grades in the final cumulative exam.

Other studies in STEM courses reported that undergraduate students infrequently utilized planned study schedules characterized by ineffective study strategies, especially cramming (Cepeda et al., 2006; Kornell and Bjork, 2007; Hartwig and Dunlosky, 2012; Blasiman et al., 2017; Geller et al., 2018; Fergus et al., 2021). Together, these findings suggest that metacognition instruction—the explicit teaching of metacognitive strategies, should be a central instructional approach in STEM courses. This is especially true for institutions that tend to serve many students from under-resourced secondary schools, where greater opportunity gaps are likely to occur (NAEP, 2020).

Undoubtedly, the metacognition equity gap—the difference in metacognitive strategies between students who have them and those who do not (McGuire, 2021), contributes to the opportunity gap. Therefore, all students must be taught how to study to enhance metacognitive equity. McGuire (2021) described metacognitive equity as “closing the gap between students who use metacognition (effective thinking and learning strategies) and those who do not” (McGuire, 2021, p. 69). According to McGuire (2021), “if metacognitive strategies could be delivered to all students at our institutions starting in the first year—if all students could be taught how to learn— then our institutions could achieve metacognitive equity” (p. 70). To better address the issues of metacognitive equity and opportunity gaps, understanding the study strategies employed by different demographic groups followed by the implementation of effective metacognitive interventions is paramount. However, very few intervention studies of this nature have been reported. For instance, Rodriguez et al. (2018) examined the students’ study practices in a molecular biology course from an intervention focused on spacing and self-testing study strategies among students from underrepresented minorities (URMs)—Hispanic/Latino, African American, and Native American students. These authors found that URMs under-utilized self-testing prior to the intervention, but the gap was partially reduced after the intervention. They also found that URMs who reported self-testing scored identical course grades as non-URMs who also self-tested, but URMs who did not self-test had a substantially larger drop in performance compared to the non-URMs who did not self-test (Rodriguez et al., 2018).

Muteti et al. (2022) investigated the effects of blending the muddiest point activities, a reinforced regulation skill, with the common formative assessments on performance in the general chemistry I course. The muddiest point activities involved asking students to write down the most confusing concepts at the end of each chapter unit using top hat technology, a digital teaching platform that acts as a student response system for real-time collection of evidence of learning, identification of gaps in learning, and obtaining feedback on the instruction (Muteti et al., 2022). These authors’ results indicated that compared to the comparison group that was exposed to the common formative assessments alone, students exposed to the muddiest point exercises and the common formative assessments combination performed significantly better in all three in-term chemistry tests, and slightly better in the final cumulative exams but the difference was not statistically significant (p < 0.05). In addition, the intervention significantly favored racially marginalized, racially marginalized-first generation, and female-first-generation students on performance in in-term exams, after controlling for incoming college preparation scores (Muteti et al., 2022).

By and large, these studies show the benefits of metacognition training in closing the opportunity gap between marginalized and non-marginalized students. However, very few studies, if any, have investigated the influence of metacognition instruction on the study strategies of college students enrolled in introductory STEM courses by demographic groups, such as gender, race/ethnicity, and first-generation status. Metacognition instruction is hereby operationalized as the explicit teaching of metacognitive strategies, which encompass metacognitive knowledge and metacognitive regulation dimensions (Flavell, 1976; Lai, 2011). Metacognitive knowledge is awareness of one's thinking or ability to identify what one knows or does not know, whereas metacognitive regulation is how one controls their thinking to facilitate learning (Flavell, 1976; Lai, 2011). Study strategies are also operationalized herein as thinking processes and habits or behaviors that students employ in their learning (Muteti et al., 2021).

Purpose of the study

In this study, the researchers sought to (1) characterize the variations in study strategies retrospectively reported by different participants demographic groups (i.e., gender, race/ethnicity, and first-generation status) in a general chemistry course prior to a 50 minute metacognition instruction, (2) investigate any variations in the reported gains in study strategies across the demographic groups immediately after the metacognition instruction, (3) investigate variations in the reported adoption of metacognitive strategies in the course across the demographic groups, and (4) examine the extent of transfer of the acquired study strategies to other courses beyond the general chemistry course across the demographics and whether the reported transfer is identical across the demographic groups. The study was guided by the following specific research questions: (1) are there variations by demographic groups, such as gender, race/ethnicity, and first-generation status in the study strategies retrospectively reported by general chemistry I students immediately after metacognition instruction compared to what they recalled their study strategies were prior to the instruction? (2) Are there variations in the reported metacognitive strategies acquired and adopted, if at all, in the general chemistry course over the semester between the demographic groups after the metacognition instruction? (3) Are there variations in the reported, acquired study strategies transferred to other courses, if at all, between the demographic groups?

Metacognition framework

The metacognition framework previously reported by the researchers (Mutambuki et al., 2020; Muteti et al., 2021) and informed by Flavell's (1976) and Lai's (2011) work was considered in this study. The framework encompasses metacognition knowledge and metacognition regulation dimensions, which are further described in Table 1.

Table 1 Metacognition dimensions, subdimensions, and descriptions

Metacognitive dimensions	Metacognitive sub-dimensions	Description
Metacognitive knowledge	Declarative knowledge	Individuals possess factual knowledge and understand their own capabilities.
	Procedural or task knowledge	Demonstrated through the application of appropriate strategies to successfully complete a given task, and strategy or conditional knowledge.
	Strategy or conditional knowledge	Involves awareness of existing strategies, how to apply them, and when and why they should be.
Metacognition regulation	Planning	Planning effective learning strategies and procedures to achieve goals; goal setting; and resource and allocation.
	Monitoring	Awareness of comprehension and task performance.
	Evaluating	Evaluating or assessing one's learning process or products from a given task.

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Context of the study

The study was conducted in the general chemistry I lecture course which was taught in conjunction with a laboratory component as described by the authors in a related study (Mutambuki et al., 2020; Muteti et al., 2021). The class met thrice a week with the majority having completed one year of high school chemistry and 15–20 percent having no prior chemical education experiences. The data for this study were collected from one lecture section, in which students were explicitly taught metacognitive strategies as well as effective study strategies and habits (Mutambuki et al., 2020; Muteti et al., 2021).

The metacognition lesson and the implementation timeline

The current study utilized the metacognitive training model previously reported by the researchers in related studies (Mutambuki et al., 2020; Muteti et al., 2021). The explicit teaching of metacognitive strategies was implemented during the second day of class through a 50 minute lesson (Mutambuki et al., 2020). Fig. 1 summarizes the timeline on the implementation of the metacognition lesson and data collection intervals. For the metacognition instruction, students were taught metacognitive strategies related to the metacognition knowledge and metacognition regulation (Flavell, 1976; Cross and Paris, 1988; Lai, 2011), and non-metacognitive, effective study strategies drawn from cognitive science research (Little and McDaniel, 2015) and discipline-based educational research (DBER) (McGuire, 2015; Stanton et al., 2015; Sebesta and Bray Speth, 2017) described in the results section.

Fig. 1 The timeline for the metacognition lesson and administering of the questionnaires addressing the research questions.

Students then completed an online homework, in which they were asked to (1) retrospectively list and describe what their study strategies/habits were prior to the metacognition lesson, and (2) describe any new study strategies they gained, if at all, after the metacognition instruction that have the potential for adoption. A retrospective account approach was employed to address research question 1. In a retrospective account, study participants are required to retrieve information from short-term or long-term memory after completing the task. For long-term memory retrieval, participants are prone to forgetting the information, leading to limited information. In addition, the approach can lead to fabrication if the process is not cued (Van Gog et al., 2005). Van Someren et al. reported that compared to plain retrospective reporting, cued retrospective reporting produced better results due to minimized forgetting or fabrication of the thoughts (Van Someren et al., 1994). The first prompt was intentionally administered immediately after the metacognition lesson rather than before the lesson to reinforce students’ reflection on their commonly employed strategies within the presented metacognition framework and study strategies and to facilitate accurate descriptions of the strategies during the reporting (Mutambuki et al., 2020; Muteti et al., 2021). In the absence of a list of techniques or study skills, or a survey offering students a selection of study techniques to pick from, students are likely to forget some techniques (Zhao et al., 2014; Chan and Bauer, 2016).

After the instruction, students were regularly reminded to utilize the metacognitive strategies and non-metacognitive strategies learned in preparation for each in-term exam (i.e., three in-term exams) and the final cumulative exam, as well as the quizzes and homework (Mutambuki et al., 2020). Prior to the in-term exam 3, students completed the second metacognitive online homework, in which they listed the study strategies that worked, and which did not work in preparation for the in-term exams 1 and 2, as well as devise a study plan for the in-term exam 3 and the final exam (Mutambuki et al., 2020). These data are beyond the scope of the current study. Students were encouraged to stick to their individually devised study plans (Mutambuki et al., 2020). The students also completed an end-of-semester, open-ended questionnaire a week prior to the final cumulative exam (Fig. 1) in which they were asked to respond to two prompts: (1) describe how the metacognition lesson helped you adjust your study strategies, if at all, in this course, and (2) describe how the metacognition lesson influenced, if at all, the transfer of the acquired study strategies to other courses beyond the General Chemistry 1 course.

Methods

Research design

This study followed the institutional review board (IRB) guidelines and the approved protocol #AS-18-157-STW obtained from the authors’ institution. The qualitative research methodology was employed to examine the study strategies employed by different demographics of students enrolled in the general chemistry I course. Open-ended questionnaires were considered for data collection rather than a structured survey, because they provided a rich opportunity to examine participants’ own descriptions of reported study strategies from a large sample without being forced to fit their strategies within the researcher's lens (Creswell and Poth, 2016).

Participants

Participants were science majors enrolled in the general chemistry I course during the Spring of 2019. Out of 270 students enrolled in the course, 259 consented to participate in the study. Of the 236 participants who provided the demographic information and completed both questionnaires before and after metacognition instruction, 72.9% were female (n = 172) versus 27.1% male (n = 64), and 72.9% were white (n = 172) versus 25.4% racially marginalized in STEM (African American), Native American, or Alaskan Hawaiian, and multiracial who most identified with the racially marginalized (n = 60). About 80.9% of the study participants were non-first-generation college students (n = 191) versus 19.1% first-generation (n = 45), whereas six participants identified as nonresident aliens. On average, no evidence was found of significant differences across the demographic groups on the ACT Math and Pre-term GPA scores, except for the first-generation status, in which the first-generation students showed significantly lower mean scores than their counterparts (p < 0.01) on both scores. A summary of these results is available in the Appendix, Table S1 (ESI†).

Data collection and analysis

For research question 1, data were collected immediately after the metacognition instruction, as online homework (Muteti et al., 2021) via the Mastering Chemistry platform, an instructor assessment editable resource (Tro et al., 2017). Data addressing research questions 2 and 3 were collected at the end of the semester through a paper-based open-ended questionnaire. To facilitate data analysis and interpretations, the metacognition framework described in Table 1 (Muteti et al., 2021) was adopted. Therefore, the deductive coding approach (Creswell and Creswell, 2017) and frequency statistics to quantify the coded strategies were employed. These study strategies are presented in Table 2. We describe the detailed coding of each research question in the subsequent section.

Table 2 Retrospective accounting of participants’ reported study strategies before and immediately after the metacognition instruction

Reported study strategies	Demographics	Reported study strategies prior to the metacognition instruction		Reported study strategies gained and potential adoption after the metacognition instruction
		% participants (n)	Cohen's h	% participants (n)	Cohen's h
Notes: Cohen's h of 0.2 is a small effect size, h = 0.5 is a moderate effect size, and h = 0.8 is a large effect size (Cohen, 1988).
LOSSs: reading and re-reading	Racially marginalized groups	51.7 (31)	0.1	3.3 (2)	0.1
	White	55.8 (96)		2.9 (5)
	Female	56.4 (97)	0.2	3.5 (6)	0.1
	Male	46.9 (30)		1.6 (1)
	First-gen	60.0 (27)	0.2	4.4 (2)	0.1
	Non-first-gen	52.4 (100)		2.6 (5)
Flashcard/quizlets	Racially marginalized groups	31.7 (19)	0.0	0.0 (0)	0.5
	White	30.2 (52)		5.8 (7)
	Female	33.7 (58)	0.2	5.2 (5)	0.0
	Male	23.4 (15)		4.7 (3)
	First-gen	37.8 (17)	0.2	6.7 (3)	0.1
	Non-first-gen	29.3 (56)		2.6 (5)
Cramming and memorization	Racially marginalized groups	13.3 (8)	0.1	—	—
	White	10.5 (18)		—
	Female	12.8 (22)	0.2	—	—
	Male	7.8 (5)		—
	First-gen	11.1 (5)	0.0	—	—
	Non-first-gen	11.5 (22)		—
Poor time management	Racially marginalized groups	26.7 (16)	0.1	—	—
	White	21.5 (37)		—
	Female	19.2 (33)	0.3	—	—
	Male	34.4 (22)		—
	First gen	22.2 (10)	0.0	—	—
	Non-first-gen	23.6 (45)
HOSSs: metacognitive strategies planning/goal setting	Racially marginalized groups	30.0 (18)	0.4	85.0 (51)	0.3
	White	51.2 (88)		93.0 (160)
	Female	45.9 (79)	0.0	94.2 (162)	0.4
	Male	46.9 (30)		81.3 (52)
	First-gen	37.8 (17)	0.2	95.6 (43)	0.2
	Non-first-gen	48.2 (92)		89.5 (171)
Reflective learning	Racially marginalized groups	13.3 (8)	0.1	69.8 (45)	0.1
	White	17.4 (30)		75.0 (120)
	Female	17.4 (30)	0.1	72.1 (124)	0.1
	Male	12.5 (8)		68.8 (44)
	First-gen	8.9 (4)	0.3	66.7 (30)	0.1
	Non-first-gen	17.8 (34)		72.3 (138)
Self-assessment	Racially marginalized groups	13.3 (8)	0.1	18.3 (11)	0.2
	White	9.3 (16)		11.6 (20)
	Female	11.6 (20)	0.2	14.0 (24)	0.0
	Male	6.3 (4)		12.5 (8)
	First-gen	2.2 (1)	0.4	20.0 (9)	0.2
	Non-first-gen	12.0 (23)		12.0 (23)
HOSSs: non-metacognitive strategies study with notetaking	Racially marginalized groups	28.3 (17)	0.1	13.3 (8)	0.1
	White	22.1 (38)		10.5 (18)
	Female	24.4 (42)	0.1	12.2 (21)	0.1
	Male	20.3 (13)		7.8 (5)
	First-gen	22.2 (10)	0.0	13.3 (6)	0.1
	Non-first-gen	23.6 (45)		10.5 (20)
Practice problems	Racially marginalized groups	18.3 (11)	0.0	11.7 (7)	0.2
	White	19.2 (33)		5.8 (10)
	Female	20.3 (35)	0.1	8.7 (15)	0.2
	Male	15.6 (10)		4.7 (3)
	First-gen	6.7 (3)	0.5	8.9 (4)	0.1
	Non-first-gen	22.0 (42)		7.3 (14)
Collaborative learning	Racially marginalized groups	6.7 (4)	0.4	13.3 (8)	0.1
	White	18.0 (31)		15.7 (27)
	Female	14.5 (25)	0.1	16.9 (29)	0.2
	Male	17.2 (11)		9.4 (6)
	First-gen	11.1 (5)	0.1	6.7 (3)	0.3
	Non-first-gen	16.2 (31)		16.8 (32)

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RQ1 was analyzed using priori categories, previously established study strategies reported by general chemistry I students in a related study (Muteti et al., 2021). The coding involved three phases. In phase 1, CZ and JMM together coded about 20% of the respondents’ responses. In phase 2, CZ continued coding the remaining responses by applying the priori categories to the relevant segments of the participants’ responses (Creswell and Creswell, 2017). In phase 3, a third researcher, BIJ reviewed the coded data to establish coherence between the generated categories and the coded participants’ responses. The interrater reliability between the two researchers was over 90% for RQ1. Discrepancies in coding were discussed and resolved by the two coders resulting in 100% agreement (Creswell and Poth, 2016). Additionally, JMM compared the generated categories against the participants’ responses for confirmation audit (Tashakkori and Teddlie, 1998), with 100% agreement reached on the categories identified during the audit and the coding.

The identified categories for RQ1 were further classified into two major categories, namely: lower-order study strategies (LOSSs) and higher-order study strategies (HOSSs). The LOSSs included rote memorization strategies, such as reading and rereading, flashcards/quizlets, and memorization or cramming, as well as poor time management. The HOSSs included metacognitive regulation strategies, such as planning and goal setting, reflective learning, self-assessment, and non-metacognitive strategies, such as studying with notetaking, practicing problems, and collaborative learning (Muteti et al., 2021).

For RQ2, reported study strategies were coded with respect to the metacognition knowledge and regulation subdimensions presented in Table 3 and previously reported in Muteti et al. (2021). RQ3 was coded as “transfer” or “no transfer” of the acquired study strategies to other courses based on the demographics by CZ and BIJ together. Examples of the reported study strategies “transferred” are presented in Table 4. For the coded strategies based on the RQs, the percentages of the participants were computed using frequency statistics. The variation in reported study strategies is the “difference in the percentage of the participants, who reported a specific strategy based on the demographic group category.” Due to small sample sizes for certain demographic groups, only variations close to or above 10% are reported for RQ1 and RQ2. Additionally, effect sizes, Cohen's h, from the proportions of respondents on the coded strategies were computed to establish the magnitude of the variation (Cohen, 1988). Findings addressing each research question are described in the subsequent section.

Table 3 Examples of reported metacognitive strategies adopted in the general chemistry I course over the semester after the metacognition instruction

Reported study strategies	Demographics (n)	% participants	Cohen's h
Notes: Cohen's h of 0.2 is a small effect size, h = 0.5 is a moderate effect size, and h = 0.8 is a large effect size (Cohen, 1988).
Metacognitive regulation strategies
Planning/class preparation/setting goals	Racially marginalized groups (6)	18.8	0.3
	White (12)	9.9
	Female (11)	9.2	0.3
	Male (7)	20.0
	First-gen (2)	6.9	0.2
	Non-first-gen (16)	12.1
Improved thinking about learning	Racially marginalized groups (3)	9.4	0.1
	White (9)	7.4
	Female (10)	8.3	0.1
	Male (2)	5.7
	First-gen (1)	3.4	0.2
	Non-first-gen (11)	8.3
Reinforced self-reflection on learning	Racially marginalized groups (1)	3.1	0.1
	White (2)	1.7
	Female (1)	0.8	0.2
	Male (0)	0.0
	First-gen (0)	0.0	0.3
	Non-first-gen (3)	2.3
Metacognitive knowledge strategies
Knowledgeable of effective study strategies	Racially marginalized groups (5)	15.6	0.0
	White (19)	15.7
	Female (22)	18.3	0.4
	Male (2)	5.7
	First-gen (5)	17.2	0.2
	Non-first-gen (20)	15.2
Applying suitable learning strategies	Racially marginalized groups (4)	12.5	0.0
	White (16)	13.2
	Female (14)	11.7	0.1
	Male (3)	8.6
	First-gen (4)	13.8	0.0
	Non-first-gen (16)	12.1
Identifying/addressing knowledge gaps	Racially marginalized groups (1)	3.1	0.4
	White (16)	13.2
	Female (17)	14.2	0.4
	Male (1)	2.9
	First-gen (2)	6.9	0.2
	Non-first-gen (18)	13.6
Improved understanding of concepts	Racially marginalized groups (1)	3.1	0.2
	White (8)	6.6
	Female (8)	6.7	0.2
	Male (1)	2.9
	First-gen (2)	6.9	0.1
	Non-first-gen (7)	5.3
Improved problem-solving approach	Racially marginalized groups (1)	3.1	0.1
	White (5)	4.1
	Female (3)	2.5	0.3
	Male (3)	8.6
	First-gen (0)	0.0	0.4
	Non-first-gen (6)	4.5

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Table 4 The reported transfer of acquired study strategies to other courses based on the demographics

Demographics	Demographic groups (% participants)	Selected participants’ responses on transfer of the acquired study strategies beyond the general chemistry course
Race/ethnicity	Racially marginalized groups (58.1%)	Sometimes I analyze what I need to work on so I could study that concept more [self-evaluation/reflection].
		Yes, I set out goals for when to start studying and what [planning/setting goals].
		The study groups helped [collaborative learning].
		Yes, in the animal bio lab, I had to think through multiple processes while discussing the [results] [strategy knowledge skill].
		Yes, the problem-solving techniques [practicing problems].
	White (54.2%)	In some ways, I focused on the information I didn’t know well [declarative knowledge skill].
		Yes, animal bio rather than memorizing organ functions and understanding how each organ plays a role in the overall system [strategy knowledge skill].
		Yes, teaching others the concept and drawing diagrams [strategy knowledge skill].
		Yes, I would step back and look at what I don’t know [declarative knowledge skill].
		Yes, in my microbiology class I tried to be aware of my thinking while learning material [declarative knowledge skill].
		Yes, I started organizing my notes in order of what I needed to work on [planning/setting goals].
Gender	Female (56.9%)	In other classes, I would practice problems. For example, in stat [statistics] I would try sample problems to test that I understood it [self-assessment].
		Yes, it helped me divide the homework into what I know and what to focus on [declarative knowledge skill].
		Yes, in Animal Bio[logy], rather than memorizing organ functions understanding how each organ plays a role in the overall system [strategy knowledge].
		Yes, I set out goals for when to start studying and what to study in other courses [planning/setting goals].
	Male (48.6%)	Yes, in my industrial CAD class, I utilized various methods to approach problems and it helped me become more efficient when working on assignments [strategy knowledge skill].
		Yes, I always thought about what I learned after the lecture [self-reflection].
		Yes, I used the learned skills to study for exams by practicing certain problems [strategy knowledge skill].
First-generation status	Non-first generation (56.1%)	Yes, I practiced more statistics problems when I struggled with them [monitoring].
		Yes, not just going over notes, but making up practice problems to quiz myself on a concept [self-assessment].
		Yes, I used my notes in class and reviewed them after to keep concepts fresh [self-reflection].
	First-generation (50.0%)	Yes, I spent time using different study strategies which helped on tests [strategy knowledge skill].
		I focused on the information I didn’t know well [declarative knowledge skill].
		Yes, reading from the book earlier, practicing the homework [planning], writing down important info [information] [self-reflection].
		Yes, Agricultural Economics. I would use the different ways of studying [strategy knowledge skill].

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Results

(RQ1) Are there variations by demographic groups, such as gender, race/ethnicity, and first-generation status in the study strategies reported by general chemistry I students immediately after metacognition instruction compared to what they recalled their study strategies were prior to the instruction?

Finding 1: considerable variations on the reported use of LOSSs prior to the metacognition instruction were noted for gender. The identified LOSSs included reading and re-reading the class notes or textbook, use of flashcards/quizlets, cramming or memorization, and poor time management. Trends on the reported study strategies prior to and immediately after the metacognition instruction by the participants’ demographics including the associated effect sizes on the computed proportions, Cohen's h, are presented in Table 2. Variations were noted for gender and first-generation status, but not for race/ethnicity. Variations by gender were noted in the reported use of reading and rereading and flashcards/quizlets, with 9.5% or more females than males reporting the use of these strategies. Moreover, 15.2% more males than females reported the use of poor time management. These variations were, however, associated with small effect sizes (Cohen's h = 0.3). There were slight to negligible variations by first-generation status and by race/ethnicity on the reported LOSSs. This finding may suggest that while females are more likely to use ineffective study strategies than males, males have poor time management habits. The findings also suggest nearly equivalent use of reported LOSSs between the first-generation and non-first-generation and between the racially marginalized groups and white participants.

Finding 2: race/ethnicity and first-generation status revealed substantive variations in the reported use of HOSSs prior to the metacognition instruction. The reported use of HOSSs included metacognitive and non-metacognitive strategies. The metacognitive strategies focused on self-regulation skills, such as planning/setting goals, reflective learning, and self-assessment. However, these strategies were reported by a few participants across all the demographic groups, except for planning/setting goals (Table 2). Substantial variations were noted in planning/setting goals by race/ethnicity and on self-assessment by first-generation status. Specifically, 21.2% more white participants compared to the participants from racially marginalized groups reported the use of planning/setting goals. For self-assessment, 9.8% more non-first generation than first-generation participants reported the use. The noted variations in these strategies were associated with effect sizes approaching moderate (Cohen's h = 0.4). There were no variations in the reported HOSSs by gender (Table 2).

The reported non-metacognitive strategies included studying with notetaking, practicing problems, and collaborative learning but were associated with low reporting across all the demographic groups. Substantial variations were based on race/ethnicity and first-generation status on the reported use of collaborative learning and practicing problems, respectively. For race/ethnicity, 11.3% more white compared to the racially marginalized groups reported the use of collaborative learning. For first-generation status, 15.3% more non-first generation compared to first-generation participants reported the use of practicing problems. The variations in the reported use of these strategies were associated with effect sizes approaching moderate (Cohen's h = 0.4–0.5). All the other reported HOSSs showed small variations between the demographic groups. This finding indicates the low use of most HOSSs reported by the participants, and the lack of evidence on the use of metacognition knowledge strategies prior to the metacognition instruction.

Overall, these findings suggest an equity gap in the reported use of specific HOSSs, metacognitive and non-metacognitive strategies, between white and racially marginalized groups, and between first-generation and non-first-generation prior to the metacognition instruction.

Finding 3: substantive variations were noted only by gender in the reported gains and the potential adoption of HOSSs—planning/setting goals immediately after the metacognition instruction. Findings indicated that a majority of all the demographic groups reported more gains on HOSSs than LOSSs immediately after the metacognition instruction (Table 2). Moderate variation was only noted for gender, in which about 13.0% more females than males reported the use of planning/setting goals. The difference in the variation was associated with nearly a moderate effect size (Cohen's h = 0.4). There were no substantive variations on other metacognitive regulation strategies reported based on the demographics. For the non-metacognitive HOSSs, variations were noted for first-generation status in the reported use of collaborative learning, with about 10.0% more non-first-generation than first-generation participants reporting the gain and the potential adoption of this strategy. However, this variation was associated with a small effect size, Cohen's h = 0.3 (Table 2). Overall, the findings showed minute variations by other demographics on all other reported HOSSs besides planning/setting goals.

These findings show the existing equity gaps identified prior to the metacognition instruction based on race/ethnicity and first-generation status were relinquished, as assessed immediately after the instruction, on the reported gains and the potential adoption of the acquired study strategies. The findings further suggest immediate growth in females’ potential adoption of planning/setting goals relative to males. Increased growth in awareness and the reported potential use of effective study strategies were also evidenced by the scanty reporting of LOSSs compared to HOSSs. However, an equity gap was noted for first-generation on the reported adoption of collaborative learning, suggesting a low likelihood of first-generation participants engaging in small-learning groups in the course.

(RQ2) Are there variations in the reported metacognitive strategies acquired and adopted, if at all, in the general chemistry course over the semester between the demographic groups after the metacognition instruction?

Findings showed that all the demographic groups reported the adoption of some form of metacognitive regulation and knowledge strategies. However, there were noted variations in some specific strategies related to the two metacognitive dimensions based on race/ethnicity, gender, and first-generation status. A summary of the reported metacognitive strategies adopted is shown in Table 3. We further articulate variations in the reported metacognitive regulation and knowledge strategies, in that order, gained and employed by the participants over the semester.

Finding 1: notable variations were evident for race/ethnicity and gender in the reported adoption of the acquired metacognitive regulation skills—planning/setting goals. The dominantly reported adoption of metacognitive regulation strategies were planning/setting goals and thinking about learning/self-monitoring, whereas self-reflection on learning was reported by a few participants or not reported by some groups (Table 3). Substantive variations were based on race/ethnicity and gender, particularly on the reported use of planning/setting goals. Specifically, about 9.0% more participants from racially marginalized groups compared to white and 10.8% more males than females reported the use of these strategies. However, these variations were associated with small effect sizes, Cohen's h = 0.3. There were neither big variations in the reported use of metacognitive regulation strategies based on the first-generation status nor on other reported regulation strategies between the demographic groups.

This finding indicates the closing of the equity gap in the reported use of planning/setting goals identified prior to the metacognition instruction based on race/ethnicity. The percentage of racially marginalized participants, who reported the adoption of these strategies in the course during the semester surpassed that of the white participants, suggesting the potential of metacognition instruction in closing the existing equity gap. Similarly, the reported adoption of these strategies by more males than females over the semester, conversely to the reported gains and the potential adoption by more females than males immediately after the instruction, indicates the potential of the metacognition instruction in addressing metacognition equity gaps. The findings further suggest that despite many participants reporting gains in reflective learning and self-assessment immediately after the metacognition instruction, there was low reported adoption of reflective learning over the semester while reporting on the use of self-assessment was absent for all the demographic groups.

Finding 2: moderate variations in the reported adoption of specific metacognitive knowledge strategies were noted for all the demographic groups. As shown in Table 3, the reported metacognitive knowledge strategies based on deductive coding included knowledgeable of effective study strategies, applying suitable learning strategies, identifying/addressing knowledge gaps, improved understanding of concepts, and knowledge of suitable problem-solving approaches in descending popularity order. For race/ethnicity, substantial variations in the reported adoption of these strategies were only noted in identifying/addressing knowledge gaps in which 10.1% more white reported the use compared to their counterparts. For gender, substantial variations were noted in knowledgeable of effective study strategies and identifying/addressing knowledge gaps, where 12.6% and 11.3% more females than males reported the use of these strategies, respectively. For first-generation status, considerable variations were noted in the reported use of improved problem-solving approach, where 4.5% more non-first generation reported the use than first-generation participants—none of the first-generation participants reported the use of strategy. The noted variations showed nearly moderate effect sizes, Cohen's h = 0.4 (Table 3). There were no substantial variations in applying suitable learning strategies and improved understanding of concepts across all the demographic groups.

These findings suggest some growth in the adoption of the reported specific metacognitive knowledge strategies acquired from the instruction by nearly all the demographic groups, especially by females. Except for the three strategies that showed variations by demographics, the negligible variations on most of the reported strategies under the metacognitive knowledge dimension across the demographic groups suggest equity in the reported use of the acquired metacognitive strategies in the course. However, the low reported adoption across all the demographic groups is alarming. By and large, these findings suggest the value of metacognition instruction in catalyzing the awareness and the adoption of metacognitive strategies across all the demographics, as well as the potential to narrow the existing metacognitive equity gaps between certain demographic groups.

(RQ3) Are there variations in the reported, acquired study strategies transferred to other courses, if at all, between the demographic groups?

Finding: no substantial variations were noted in the reported transfer of study strategies to other courses based on the demographic groups. Eighty-eight out of 164 questionnaire respondents (53.7%) reported they applied the study strategies acquired from the instruction to other courses during the same semester, whereas 71 respondents (43.3%) did not transfer the learned strategies (Table 4). The non-responses were five (3.0%). The findings indicated only slight variations in the reported transfer of the acquired strategies by first-generation status (6.1%), gender (5.5%), and race/ethnicity (3.9%). Specifically, the reported transfer by the demographic groups was 56.1% (N = 69) non-first generation versus 50% (N = 14) first-generation, 56.9% (N = 66) female versus 48.6% (N = 17) male, and 58.1% (N = 18) racially marginalized groups versus 54.2% (N = 64) white. These variations were also associated with small size effects (Cohen's h = 0.1–0.2) as shown in the Appendix, Table S2 (ESI†). Table 4 also shows examples of the participants’ responses illustrating the reported transfer of acquired study strategies, including specific metacognitive knowledge and regulation skills to other courses. The participants’ descriptions revealed a sustained use of HOSSs beyond the general chemistry course by slightly over half of the study participants from all the demographic groups, except the males and first-generation participants.

Discussion and conclusions

Discussion

The goal of the study was to determine if the explicit teaching of metacognitive strategies enhanced equity in the reported study strategies between student demographic groups, gender, race/ethnicity, and first-generation status in the general chemistry I course. Findings by gender showed that prior to the metacognition lesson, there was no variation in the reported use of HOSSs, but there was evidence of a potential equity gap in the reported use of LOSSs—reading and rereading and flashcards/quizlets, with more reported use by females than males. However, there were no variations in the reported potential adoption of these strategies by gender immediately after the metacognition instruction. This finding contradicts other studies that found more males than females reported the use of reading and re-reading (Alzahrani et al., 2018; Williams et al., 2021). For instance, Alzahrani et al.'s, 2018 study surveying the study habits such as study time, study partners, source of study, breaks, study interruptions, difficulty concentrating, study activity, and delayed study at the College of Medicine and Applied Medical Science at Taif University reported that 78% of male students preferred studying by repeated reading compared to 65% of the female students (Alzahrani et al., 2018). However, current findings on flashcards align with those reported by Williams et al. (2021). From their survey conducted with a total of 1815 students at a public research university in the United States, Williams et al. found that the use of flashcards was more commonly reported by women than male participants (Williams et al., 2021).

Furthermore, in contrast to other studies that showed more females than males reported the use of goal setting, organization, and planning (Zimmerman and Martinez-Pons, 1990; Hagborg, 1991; Ossai, 2012; Salami, 2013), the current findings showed that the reported use of planning/setting goals was nearly identical for the gender groups prior to the metacognition. However, more females reported gain and the potential adoption of this strategy immediately after the metacognition instruction but lapsed in its adoption in the course over the semester compared to males. In addition, the finding might suggest growth for males toward planning/setting goals over the course of the semester, but unsustainable use by females; thus, a need for continuous coaching of students on metacognition regulation strategies. Current findings on reflective learning are consistent with those reported by Ottenberg et al. (2016). These authors administered a modified version of the Reflection Evaluation for Learners’ Enhanced Competencies Tool (REFLECT) on writing samples about professionalism in gross anatomy with first-year medical students. Their findings indicated that females had higher mean composite reflection scores than male students (Ottenberg et al., 2016).

Findings on the reported non-metacognitive strategies showed no variations by gender which contradict those reported by others (e.g., Risch and Kiewra, 1990; Ossai, 2012; Salami, 2013) who found that females were more likely to use better study skills, take notes while studying, and do practice problems using their textbook (Charles-Ogan, 2015) than males before and immediately after a metacognition intervention. Additionally, although others reported that females were more likely than males to study with a colleague (Al-Shawwa et al. 2014) or preferred engaging in a small-learning group (Benditz et al. 2018), the current study showed no substantial variations in the reported use of collaborative learning by gender prior to and immediately after the metacognition instruction.

The reported adopted metacognitive knowledge strategies over the semester (RQ2) showed notable variations in knowledge of effective study strategies and identifying/addressing knowledge gaps, with more females than males reporting the use. This finding suggests growth in the awareness and utility of the metacognitive strategies by females partly due to the instruction. Given that the participants relied on recall of the adopted strategies gained from the instruction, future studies should consider administering a survey focused on the study strategies described herein to elicit reflection on specific strategies and gauge the degree to which they are employed before, immediately, and after several months of implementing the metacognition instruction.

Findings based on race/ethnicity showed no variations in the reported use of LOSSs, but potential evidence of equity gap in reported HOSSs, such as planning/setting goals and collaborative learning prior to the metacognition lesson. This gap was, however, closed after the metacognition instruction. In contrast to Williams et al.'s (2021) findings, which reported the low use of flashcards and reading and re-reading by racially marginalized groups compared to their counterparts, the reported use of these LOSSs in the current study was nearly identical between the two racial/ethnicity groups prior to the metacognition instruction. However, fewer racially marginalized groups reported engagement with collaborative learning than their counterparts. These variations can partly be due to marginalized groups being at risk for accessing social capital (Terenzini et al., 1996), a network of relationships that afford support to thrive in an unfamiliar environment by providing valuable information, and social and emotional support (Stanton-Salazar, 2001). Students’ interactions with instructors and their peers have a positive impact on their intellectual development and personal growth (Pascarella et al., 2004). However, if not well structured and governed by participation rules, group learning can elicit stereotype threats, which to a greater extent negatively impact women and minority ethnic groups compared to their counterparts. As such, marginalized students in STEM may be uncomfortable seeking help from peers and instructors of different identity groups (Stanton-Salazar, 1997; Foor et al., 2007; Thiem and Dasgupta, 2022). The literature indicates that self-assessment/self-testing is a strategy used by many students (Hartwig and Dunlosky, 2012; Morehead et al., 2016), “but tend to be less utilized by minority racial/ethnic groups” (Rodriguez et al., 2018; Williams et al., 2021). The current study, however, showed no substantive variation by race/ethnicity on the reported use of this study strategy, even though slightly more racially marginalized groups reported the use prior to and immediately after the instruction compared to white participants, and no reported adoption in the course over the semester by both racial groups.

Based on first-generation status, results showed no variations in the reported use of LOSSs, but a potential evidence of equity gap in the reported HOSSs—self-assessment and practice problems prior to the metacognition lesson. This gap, however, closed completely following the metacognition instruction. Surprisingly, the reported adoption of these metacognitive regulation strategies and self-monitoring or thinking about learning was minimal over the course of the semester, with self-assessment not at all reported. Similar to other demographics, the reported gains and the potential use of LOSSs in the course by both groups decreased drastically immediately after the metacognition instruction. The reported dominant use of LOSSs prior to the instruction across the demographics indicates a lack of awareness of metacognitive and effective study strategies by the study participants in the General Chemistry I course (Muteti et al., 2021). Conversely, the drop in the reporting of the LOSSs suggests participants’ increased awareness of these ineffective study strategies in mastering concepts in the course after the instruction.

There is a consensus that the acquired metacognitive strategies and skills can be transferred across disciplines and subjects (Schraw, 1998; Veenman and Verheij, 2003; Veenman et al., 2004). The current study confirmed these contentions, as no variations in the reported transfer of the learned and acquired strategies to other courses based on the demographics were noted. But, slightly more than half of the males and half of the first-generation participants reported the transfer of strategies to other courses compared to their counterparts and other demographic groups. Follow-up interviews can be employed in future studies to probe the reasons for the low reported transfer of the acquired study strategies by males and first-generation status.

Conclusions

This study reveals variations in the reported use, gains, and adoption of specific study strategies (LOSSs and HOSSs) by gender, race/ethnicity, and first-generation status prior to and after the metacognition instruction, suggesting the existence of equity gaps in awareness, and/or the use of effective study strategies. The equity gaps prior to the instruction were evidenced on the reported LOSSs, where rote memorization strategies (i.e., reading and re-reading and flashcards/quizlets) were reported by more females and first-generation participants compared to their counterparts, and poor time management by more males than females. Equity gaps in HOSSs were noted in the reported use of planning/setting goals and engagement in collaborative learning by more white participants compared to the racially marginalized groups, engagement in self-reflection and practicing problems by more non-first generation than first-generation participants.

Nevertheless, findings revealed the potential impact of the metacognitive instruction in increasing participants’ awareness of and the potential adoption of effective study strategies and in drastically decreasing the reported LOSSs across all the demographic groups (Table 2). The instruction also facilitated the narrowing or closing of the identified equity gaps in specific study strategies between the demographic groups that showed substantive variations (Tables 2 and 3). Additionally, there were noted variations in the reported study strategies immediately after the instruction, revealing growth in the potential adoption of specific HOSSs by certain groups partly due to the instruction. For example, while there was no substantial variation noted prior to the metacognition instruction, more females than males reported the potential use of planning/setting goals, and more first-generation than non-first-generation participants reported the potential use of collaborative learning in the course immediately after the instruction. The noted variations associated with the effect sizes approaching moderate also suggest that metacognition instruction not only can increase students’ awareness of HOSSs but has also the potential to catalyze equity in effective study strategies across student demographic groups in the introductory STEM courses, such as general chemistry.

Findings on the reported adoption of the acquired study strategies in the course over the semester indicated variations by gender and race/ethnicity on planning/setting goals, suggesting sustainable use of these regulation skills by females, and closure of identified equity gap prior to the instruction, with the metacognition instruction benefiting more racially marginalized groups. However, the findings showed that more female, non-first-generation, and white participants reported the adoption of metacognitive knowledge strategies compared to their counterparts. The nearly moderate effect sizes associated with these variations suggest a potential equity gap between the demographic groups and the need for continuous student coaching on metacognitive knowledge strategies.

Finally, the findings revealed that students across all the demographic groups reported the transfer of study strategies learned and acquired from the instruction, particularly HOSSs—metacognitive strategies and non-metacognitive strategies, beyond the intervention course. Moreover, there were no substantial variations noted, suggesting the potential influence of metacognition instruction in facilitating equity and the cross-pollination of effective study strategies in STEM courses.

Limitations of the study

This study has some shortcomings. First, retrospective reporting was employed in addressing RQ1 which can lead to skewed results (Van Someren et al., 1994; Van Gog et al., 2005). To ascertain the reproducibility of the current findings, future studies can modify the data collection procedures, in which participants can be asked to describe the study studies they commonly use followed by the presentation of the lesson on study strategies. Secondly, the study utilized the qualitative methodology and therefore, the findings are transferrable but not generalizable beyond the study population. Additionally, while qualitative methodologies provide rich opportunities for describing a phenomenon, self-reported data may generate inaccurate results on the actual experiences or practices employed by the participants as participants might underestimate or overestimate their study strategies—Dunning-Kruger effect (Kruger and Dunning, 1999). Therefore, there is a critical need to replicate the current study by involving similar student demographic groups from other institutions for the same course and other introductory STEM courses. Moreover, future studies should therefore utilize data triangulation, such as open-ended surveys, interviews, and structured surveys to secure the credibility of self-reported data (Creswell and Poth, 2016). Finally, the sample size across the demographic groups is unequal, even though the study samples from first-generation and racially marginalized groups are likely to be representative of the student populations in the general chemistry courses at other equivalent R1 minority-serving institutions.

Implications for practice

The findings imply several considerations for improving study strategies in introductory STEM courses that attract students from diverse populations. First, instructors should recognize the existence of equity gaps in the use of effective study strategies across student demographic groups and adapt their instruction accordingly to cater to the needs of students, especially women, first-generation, and those from racially marginalized groups. Second, the low reported use of metacognitive strategies across all the demographic groups prior to the instruction implies the lack of knowledge or awareness of metacognition among college students who enroll in STEM programs. These findings imply the need to explicitly teach metacognition to students in introductory college STEM classrooms. Importantly, socializing students with metacognitive strategies early during K-12 education can facilitate the attainment of metacognitive equity between vulnerable and non-vulnerable student populations (McGuire, 2021). To catalyze metacognition awareness in K-12 schools, pre-service teacher training programs should consider incorporating metacognition training in the teaching methods courses and model the skills for pre-service teachers through experiential learning in lesson planning and teaching practice.

Furthermore, in-service teachers, college STEM instructors, and future faculty unfamiliar with metacognition can benefit from professional teaching development workshops focused on metacognition. Specifically, teaching center units can leverage the University-wide orientations for new faculty and graduate teaching assistants (GTAs) to increase awareness of metacognition and integration into the curricula and instruction. In turn, this will facilitate students’ awareness of effective HOSSs at their disposal and narrow the metacognition equity and opportunity gaps between marginalized and non-marginalized student populations. For instance, Muteti et al. showed that incorporating planned metacognition regulation, such as muddiest point activities at the end of each chapter can bolster the performance of all students, especially the racially marginalized groups, racially marginalized first-generation, and female first-generation students in the general chemistry tests (Muteti et al., 2022).

Freshmen seminar courses and bridge courses that serve underprepared students can also be structured to include opportunities for metacognition instruction. Moreover, supplemental peer instructors and undergraduate academic advisors can benefit from metacognition training to guide students on the right path toward identifying and employing suitable study strategies for different courses. In college, students enroll in multiple courses that often require varying study strategies, when learning factual versus conceptual or cognitively demanding concepts (Mutambuki et al., 2020). Therefore, they ought to be metacognitively aware of which strategies to employ, when, where, and why to employ them. Unfortunately, students who lack metacognitive skills are likely to tussle with such decisions. The current study showed that 50% of the first-generation and 51.4% of male study participants reported they did not transfer the learned study strategies to other courses. Thus, supplemental tutors/peer leaders and academic advisors can step in and assist in training undergraduate students on metacognitive skills. In turn, students can begin to recognize variations or overlaps in study strategies across different STEM courses and facilitate the transfer of relevant strategies to disciplines that require similar thinking skills.

Lastly, with student buy-in to metacognition instruction, the acquired metacognitive strategies can be transferrable to other courses. However, continuous coaching and nurturing on metacognitive regulation and metacognitive knowledge strategies may increase the value and utility of the learned metacognitive skills/strategies in multiple courses, especially among first-generation students and males who showed more reluctance to adopt metacognitive strategies beyond the course. Specifically, including metacognition prompts in formative assessments, such as homework, quizzes, and practice exercises can catalyze engraining of the metacognitive strategies in long-term memory for sustainable use. Metacognitive activities, such as one-minute paper and application card activities (Angelo and Cross, 1993; Nilson, 2016), among others, can be embedded in the instruction to foster self-reflection skills. In a one-minute paper activity, students summarize the most important points they learned from the day's lesson and the questions that remain unanswered. In application cards, students write down how the concepts they learned from a given lesson apply to their daily experiences or real-world applications (Angelo and Cross, 1993; Nilson, 2016). Therefore, these activities reinforce students’ reflections on learning.

Conflicts of interest

The authors declare no competing financial interest.

Acknowledgements

This work was in part supported through the Edward E. Bartlett Endowed Chair fund at Oklahoma State University.

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Footnote

† Electronic supplementary information (ESI) available: Appendix. See DOI: https://doi.org/10.1039/d3rp00103b

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