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Predicting learning: Comparing an open educational resource and standard textbooks.

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Abstract

Open educational resources (OERs) enable anyone, anywhere, to access psychological science for free. Are OERs as effective learning tools as standard textbooks (STBs)? I compared students using an OER with students using STBs in 2 large, multisite studies (N = 1,099 and N = 2,229, respectively). Studies measure key student variables and possible confounds such as metacognition, study techniques, time spent studying, perceptions of the instructor, and rating of the quality and helpfulness of the textbook. Students completed a standardized test using a subset of items from a released Advanced Placement exam. In both studies, OER users reported lower ACT scores. In Study 1, students using an OER scored lower on the test after controlling for ACT scores, F(1, 777) = 48.09, p < .001, ηp2 = .06, and rated the book as lower in quality. Scores on book helpfulness did not vary between groups. Study 2 also compared book format (hard copy or electronic) and showed a main effect of book used, no main effect of format, and a significant book used by format interaction effect, F(2, 1406) = 5.29, p = .005, ηp2 = .01: OER hard copy users scored lowest. Book used predicted significant variance in learning over and above ACT scores and student variables (STB users performed better). The results highlight limitations of current attempts to assess learning in psychology and underline the need for robust comparisons of a wider variety of OERs, with a focus on lower ability students, and e-book usage patterns.

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... A backward search of the reference lists of reports found and a forward search of work that had cited found reports was then conducted. This led to a selection of seven reports for this review (one of which contained two studies; Gurung, 2017b). An eighth report was recommended by an anonymous reviewer. ...
... Student outcomes in OER research has typically focused on performance measures in their courses, such as overall grade, passing rates, and exam grades. However, there was one study in which performance on a standardized assessment chosen by a researcher was compared between students enrolled in courses with OER and those using commercial textbooks (Gurung, 2017b). In terms of results, two studies on performance favor OER (although they may be limited to certain measures), two studies found no differences between OER and commercial materials, and two studies favored commercial materials. ...
... In addition, the type of OER and/or commercial textbooks used may explain the conflicting findings between Robinson (2015) and Fischer et al. (2015), but details about the materials were not provided in either report. Gurung (2017b) conducted a multi-institution study comparing Introduction to Psychology students enrolled in courses using an open textbook (Noba; Biswas-Diener & Diener, 2014) to those in courses with commercial textbooks. Instead of examining learning outcomes based on course grades, Gurung (2017b) used researcher-chosen measures in two separate studies, one based on the Psychology Advanced Placement exam and the second on the Noba testbank, both of which students completed online. ...
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Open educational resources (OER) have been developed to free students from the expense and instructors from the restrictions of commercial materials. There has been a wealth of empirical examination on numerous aspects of OER. The purpose of this narrative review is to synthesize and integrate the findings on OER in psychology to assist instructors in making informed decisions about course materials. Topics in this review were organized according to the Cost, Outcomes, Usage, and Perceptions framework. Results indicated that OER adoption yielded cost savings while generally having similar or better outcomes in terms of grades. Students typically reported similar use and perceptions of OER compared to commercial course materials. Resources for instructors interested in OER are described. Criticisms of OER, such as concerns about quality, are addressed as well as limitations of reviewed research and future directions for research and development of OER.
... Other studies of larger scale show mixed effects of OER, with one study (Gurung, 2017) reporting lesser performance on learning and biopsychology quiz items when OER versus traditional textbooks were used, and two others reporting improved outcomes with OER use. In Biology, History, Psychology, and Sociology courses for over 10,000 students at a large State university, Colvard and colleagues (2018) showed that course grades increased and rates of nonproductive grades (i.e., earning a D or F grade, or a W for course withdrawal) decreased for students who typically are at risk in college (e.g., part-time students, students who received Pell grant) when OER was adopted. ...
... The neutral outcome is consistent with most prior work on OER (e.g., Clinton, 2018;Hilton, 2016;Wang & Wang, 2017) and inconsistent with prior work reporting positive (Weller et al., 2015) and negative (Gurung, 2017) impacts of OER. Clinton (2018), in another study of undergraduates at a regional State university, reported similar outcomes for students when OER and commercial textbooks were used; further, students in that study -like ours and in French et al. (2015) -indicated their likelihood of using the course resources and perceived quality of resources were similar regardless of whether the resources were costly or free. ...
... Recall that only two negative comments about OER materials in the present study involved student's desire for print materials. While "professionalization" is critical for students to perceive them as credible (Bliss et al., 2013, Gurung, 2017, OER also should be mobile friendly (Ally & Samaka, 2013). Finally, web-based supplements (e.g., StatHand, Allen et al., 2019) can enrich streamlined open-access textbooks. ...
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Research methods course(s), a standard in psychology programs, often use multiple textbooks to address conceptual and data-analytic information. This study involved transitioning from traditional textbooks to open educational resources in a research methods course. Two psychology instructors, each offering course sections, identified open-access textbooks that aligned with course learning objectives and developed instructional materials to accompany those textbooks. All materials were organized publicly in an institutional subject guide. We compared students’ grades, pretest-posttest scores, and survey reports of resource use and evaluation in a spring semester, when traditional/costly textbooks were used, to the following fall semester, when no-cost textbooks were used. Student grades and pretest-posttest growth, and reported use and ratings of course materials, were similar across semesters. Though the present findings are limited in scope, they suggest that no-cost resources can be used successfully for teaching research methods with minimal transition difficulties and without student learning deficits.
... However, other researchers (e.g. Gurung, 2017b) have reported that the format of the book (print vs. electronic) can contribute to significant differences in quiz performance on specific topics of psychology. These findings suggest that despite offering an alternative and often cheaper means to access course content, electronic textbooks may not be equally effective for all students or all content areas. ...
... More recent work has attempted to address many of these original confounds. While some researchers have found that the use of OER is associated with improved (Bliss, Robinson, Hilton, & Wiley, 2013;Colvard, Watson, & Park, 2018) or worsened (Gurung, 2017b) outcomes, most research has found OER to be equivalent to traditional textbooks (e.g. Hendricks, Reinsberg, & Rieger, 2017;Jhangiani, Dastur, Le Grand, & Penner, 2018;Watson, Domizi, & Clouser, 2017). ...
... Those that have (e.g. Fischer, Hilton, Robinson, & Wiley, 2015;Hilton & Laman, 2012;Robinson, 2015) have typically included confounds or have only examined specific topic areas of psychology (Gurung, 2017b). Most recently, Jhangiani and colleagues (2018) compared psychology student performance using traditional or OER textbooks, but acknowledged that the two textbooks differed in content, structure, and style. ...
Article
Open Educational Resources (OER) remove barriers to access instructional material. In light of their increased availability and use, a body of research has emerged to examine the impact of OER on college student success. While many of these studies have broadly examined efficacy across a variety of disciplines, the current study specifically examined the impact of the type of textbook (commercial vs. OER) on course content mastery within an undergraduate sample of introductory psychology students (N = 63) while controlling for instructor and student differences. Results indicated that there were no significant differences in content mastery between those students in introductory psychology courses who were assigned a traditional commercial textbook and those who were assigned an OER textbook. These results support that OER can be equally effective as traditional, commercial textbooks and have implications for course material selections that help ensure access for all students.
... Similarly, Pawlyshyn et al. (2013) reported dramatic improvement when OER was adopted; however, the OER adoption came simultaneously with flipped classrooms, making it difficult to correlate changing efficacy and OER. These critiques have been raised by other researchers (Gurung 2017;Griggs and Jackson 2017). ...
... It is also possible that students tend to have an overall positive experience in every class they take thus causing them to rate most classes as "better" than a typical class, even though this is not mathematically possible. Gurung (2017), used a short version of the Textbook Assessment and Usage Scale (TAUS; Gurung and Martin 2011) to assess student perceptions of CT and OER. The TAUS is assesses different components of a textbook, such as study aids, visual appeal, examples, and so forth. ...
... The TAUS is assesses different components of a textbook, such as study aids, visual appeal, examples, and so forth. Gurung (2017) asked students to rate the current textbook they were using (some subjects used OER and others used CT) and compared the results. In his first study, Gurung found CT users rated the total quality of their textbook as higher than those using an OER textbook. ...
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Although textbooks are a traditional component in many higher education contexts, their increasing price have led many students to forgo purchasing them and some faculty to seek substitutes. One such alternative is open educational resources (OER). This present study synthesizes results from sixteen efficacy and twenty perceptions studies involving 121,168 students or faculty that examine either (1) OER and student efficacy in higher education settings or (2) the perceptions of college students and/or instructors who have used OER. Results across these studies suggest students achieve the same or better learning outcomes when using OER while saving significant amounts of money. The results also indicate that the majority of faculty and students who have used OER had a positive experience and would do so again.
... Many studies have examined differences in learning performance as well as course withdrawal rates between open and commercial textbooks (see Hilton, , 2018, for reviews). However, results have been mixed with some showing positive results (Colvard, Watson, & Park, 2018;Hilton, Fischer, Wiley, & Williams, 2016), some showing negative results (e.g., Gurung, 2017), and some showing no difference between commercial and open textbooks (Allen et al., 2015;Grissett & Huffman, 2019;Medley-Rath, 2018). The purpose of this article is to meta-analyze the research findings comparing learning performance and course withdrawal rates between open and commercial textbooks. ...
... 2 These concerns are not unwarranted. Indeed, in two studies comparing performance on researcher-developed, objective learning measures, students enrolled in courses with commercial textbooks outperformed students enrolled in courses with open textbooks (Gurung, 2017). However, there have been numerous studies on open textbooks indicating no meaningful differences in learning compared with commercial textbooks (e.g., Clinton, 2018;Engler & Shedlosky-Shoemaker, 2019;Jhangiani, Dastur, Le Grand, & Penner, 2018;Medley-Rath, 2018) that need to be considered alongside Gurung's (2017) findings. ...
... Indeed, in two studies comparing performance on researcher-developed, objective learning measures, students enrolled in courses with commercial textbooks outperformed students enrolled in courses with open textbooks (Gurung, 2017). However, there have been numerous studies on open textbooks indicating no meaningful differences in learning compared with commercial textbooks (e.g., Clinton, 2018;Engler & Shedlosky-Shoemaker, 2019;Jhangiani, Dastur, Le Grand, & Penner, 2018;Medley-Rath, 2018) that need to be considered alongside Gurung's (2017) findings. For this reason, a meta-analysis in which the overall efficacy of open textbooks across studies were summarized would be informative for instructors, administrators, and policymakers. ...
Article
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Open textbooks have been developed in response to rising commercial textbook costs and copyright constraints. Numerous studies have been conducted to examine open textbooks with varied findings. The purpose of this study is to meta-analyze the findings of studies of postsecondary students comparing learning performance and course withdrawal rates between open and commercial textbooks. Based on a systematic search of research findings, there were no differences in learning efficacy between open textbooks and commercial textbooks (k = 22, g = 0.01, p = .87, N = 100,012). However, the withdrawal rate for postsecondary courses with open textbooks was significantly lower than that for commercial textbooks (k = 11, OR (odds ratio) = 0.71, p = .005, N = 78,593). No significant moderators were identified. Limitations and future directions for research, such as a need for more work in K–12 education, outside of North America, and that better examine student characteristics, are discussed.
... Though tuition is a clear contributor to the cost of a college education, non-tuition college expenses such as textbooks, housing, and other essential needs often exceed the cost of tuition (California Student Aid Commission, 2019). The rising cost of tuition and fees may not be offset by available financial aid (Florida Virtual Campus, 2019), leaving students with difficult decisions about purchasing required course materials, working more, or cutting back costs by way of other vital needs (Gurung, 2017;Broton and Goldrick-Rab, 2018). ...
... Usage research explores how faculty and students engage with OERs, such as evaluating student engagement with OERs and covarying learning outcomes (Gurung, 2017;Clinton, 2018;Cuttler, 2019). Related to studies explore pedagogical techniques made possible by OER (Wiley and Hilton, 2018), such as student generated or remixed OERs (Randall et al., 2013;Azzam et al., 2017;Jhangiani, 2017), and the open sharing of instructional design and pedagogical techniques (Cronin, 2017). ...
... These studies may also evaluate a variety of other use and outcome variables. For instance, Gurung (2017) recruited 1,099 students taking psychology courses at seven institutions and evaluated student satisfaction with the text assigned by their institution, student perception of their class and learning experiences, student performance on a 15-item quiz, and student prior academic achievement (operationalized using ACT standardized college admission test scores). Commercial textbook users reported higher ACT scores, but less satisfaction with learning and with their course. ...
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Prior studies on students’ perception of open educational resources (OERs) indicates that students find open resources as good or better than commercial textbooks (Hilton, 2016). However, studies published to date have not attempted to control for student knowledge of cost as a variable influencing perception of quality. The purpose of this study was to evaluate students’ perception of the quality of brief, de-identified open and commercial textbook samples, then determine whether their preferences changed after learning textbook costs. As part of an in-class activity, students enrolled in an introductory-level psychology course reviewed samples of two commercial and two open textbooks. Participants rated the materials on quality measures (Gurung and Martin, 2011), selected a preferred textbook, and provided a rationale for their choice. Next, participants were informed of the cost of each textbook and asked to re-rate textbook quality and indicate whether their textbook preference had changed. Prior to learning the cost of the textbooks from which each sample was selected, 81.29% of responding participants indicated preference for a specific commercial text, citing quality factors related to quality/clarity of writing, book layout, and quality of figures as primary drivers of preference. Following the cost reveal, only 42.46% of responding participants indicated a preference for a commercial textbook while 57.53% indicated a preference for an open textbook. An exact McNemar’s test determined that this was a statistically significant difference in the proportion of respondents who selected open and commercial texts before and after price data were available, p < 0.01. Qualitative comments for participants who indicated a preference shift toward the open textbook referenced cost and quality of the materials as components of their decision-making, supporting previous studies that demonstrate cost is an important predictor of students’ textbook preferences (Clinton, 2019). Regression analysis showed that visual appeal, engaging writing, and clarity of writing predicted participants’ desire to use the text in class, but quality of examples was only a significant predictor for one of four texts. Suggestions for future research are discussed.
... However, a large study comparing multiple disciplines found a benefit for open textbooks over commercial textbooks in terms of final grades, especially for students who were categorized as lower in socioeconomic status based on financial aid eligibility (Colvard et al., 2018). Nevertheless, when expanding comparisons to students at different institutions, at least one study has noted poorer learning performance for students in courses using open textbooks (Gurung, 2017). ...
... One issue is that a substantial portion of these studies did not hold the instructor and course constant (Clinton and Khan, 2019), which is problematic as teaching quality and grading criteria vary by instructor (de Vlieger et al., 2016). Additionally, the learning performance measures in studies often varied for courses with open compared to commercial textbooks (see Gurung, 2017, for exceptions). The issue of objective, identical measures is notable given that Gurung (2017) found students enrolled in courses with open textbooks did less well on objective measures of learning than did students in courses with commercial textbooks. ...
... Additionally, the learning performance measures in studies often varied for courses with open compared to commercial textbooks (see Gurung, 2017, for exceptions). The issue of objective, identical measures is notable given that Gurung (2017) found students enrolled in courses with open textbooks did less well on objective measures of learning than did students in courses with commercial textbooks. ...
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Open textbooks, which provide students with electronic access to texts without fees, have been developed as alternatives to commercial textbooks. Building on prior quasi-experiments, the purpose of this study is to experimentally compare an open and commercial textbook. College students (N = 144) were randomly assigned to read an excerpt from an open or commercial textbook, answer questions about content, and indicate their perceptions of textbook quality. Learning was similar between textbook types. Perceptions differed in that the discussion of research findings was reported as higher quality in the open textbook while the visuals and writing were reported as higher quality in the commercial textbook. Neither perceptions of research findings nor visuals correlated with learning performance. However, perceptions of writing quality and everyday examples were correlated with learning performance. Findings may inform initiatives for open textbook adoption as well as textbook development, but are limited due to the use of an excerpt. Reading to learn is a fundamental activity for knowledge construction (Duke et al., 2003; Alfassi, 2004; Maggioni et al., 2015). Textbooks are common educational tools for reading to learn, even in the digital age (Fletcher et al., 2012; Knight, 2015; Illowsky et al., 2016). The rising cost of commercial textbooks, along with the affordances of the internet and growing interest in expanding access to knowledge, has brought about the development of open textbooks, which students can access electronically without cost (Smith, 2009). There have been multiple studies indicating that students' learning from and opinions of open textbooks are similar to or better than those of commercial textbooks (e.g., Clinton, 2018; Lawrence and Lester, 2018; Medley-Rath, 2018; Cuttler, 2019; Grissett and Huffman, 2019). However, these studies have all been quasi-experimental or correlational; therefore, causal claims were not possible. Moreover, students in these studies were aware that the open textbooks were free whereas the commercial textbooks were not, which could bias their attitudes (Clinton, 2019). An experimental examination with participants who are naive to the cost of the textbook would address the confounds related to student awareness of cost. The purpose of this experiment is to examine students' learning from and perceptions of an open textbook compared to a commercial textbook.
... The recent increase in use of electronic textbooks and open educational resources (OERs) has created a need to study the efficacy of these materials in relation to student use and learning. Recent research has indicated that even with a growing comfort with electronic media, students still prefer traditional textbooks to their electronic counterparts (Woody, Daniel, & Baker, 2010 (Griggs & Jackson, 2017;Gurung, 2017). In one carefully designed study, Gurung (2017) found that introductory psychology students spent significantly less time studying from OERs than printed text, a finding in contrast to studies examining electronic versus printed textbooks. ...
... Recent research has indicated that even with a growing comfort with electronic media, students still prefer traditional textbooks to their electronic counterparts (Woody, Daniel, & Baker, 2010 (Griggs & Jackson, 2017;Gurung, 2017). In one carefully designed study, Gurung (2017) found that introductory psychology students spent significantly less time studying from OERs than printed text, a finding in contrast to studies examining electronic versus printed textbooks. Additionally, the author reported OER users scored lower on quiz questions drawn from the standardized advanced placement psychology exam. ...
Article
Time on task has been recognized as an important variable in academic learning, but self‐report measures of study time are problematic. Therefore, this study employs an automated system for recording time spent reading a course textbook. College students in an introductory engineering course accessed their textbook online. The book contained pages of instructional text, worked examples, homework problems, and answers to homework problems. An instrumented document reader program called “STL Reader” recorded the time each student spent on each page, thus providing detailed measures of reading habits. Across the 10‐week course, students spent an average of 1.9 hr reading instructional text, 1.4 hr on worked examples, 22.1 hr on homework problems, and 0.9 hr on homework answers, indicating a preference for practicing to solve test problems (i.e., self‐testing) rather than being told (i.e., receiving direct instruction). Furthermore, course grade (based largely on solving problems on exams and quizzes) correlated significantly and positively with time viewing homework problems, but not with time viewing either instructional text or worked examples, indicating that achievement was related to time spent practicing for solving test problems but not to time spent being instructed. Results suggest a revision of the time‐on‐task hypothesis to include the value of spending time on tasks aligned to test requirements. Lay Description What is currently known?: • Time‐on‐task theory states that students' time engaged in relevant material is an important factor in learning and achievement. • How students choose to process presented information is important for academic learning. • Undergraduate STEM students often read very little of the assigned course textbook. What this paper adds: • Technology‐enhanced data collection provides more accurate measure of students' engagement with e‐textbook. • Time spent viewing homework problems is significantly and positively related to achievement in an undergraduate engineering course. • Student grades were not positively correlated with time spent viewing instructional text or worked examples from the textbook. Implications: • Suggests revision of time‐on‐task hypothesis to include the value of spending time on tasks aligned to test requirements.
... Research testing OER and publisher books is still in its infancy, mostly because of the many factors to control for in multisite studies, and has many confounds (Griggs & Jackson, 2017). One large multisite national study found students using standard textbooks performed better on questions taken from an AP exam than students using an OER (Gurung, 2017). Other studies (not in psychology) using standardized or similar exams show no differences in exam scores between OER and publisher book users (Allen, Guzman-Alvarez, Molinaro, & Larsen, 2015). ...
... The current state of pedagogical research on Intro Psych shows few exemplars of these standards. Whereas a handful of studies have included more than one institution (e.g., Gurung, 2017) or are longitudinal in nature (McCarthy & Frantz, 2016), most existing research does not employ such methodologies. ...
Article
The introductory psychology (Intro Psych) course is the bedrock of the psychology major and the front face of our discipline. The class not only provides a foundation for students in the major but also provides a comprehensive portrait of the discipline for nonmajors. Despite a sizable body of research focused on pedagogy related to the introductory class, there are many questions that remain unanswered. We provide a comprehensive review of scholarship related to the Intro Psych course and discuss current practices and concerns related to textbook options, as well as teaching methods, course design, assignments to help students learn, and students’ learning outcomes. Finally, we provide five major suggestions for future work. We charge researchers to identify major bottlenecks to learning, design multisite studies, measure moderators of learning, assess long-term retention, and design/assess different models of teaching Intro Psych.
... Rather than asserting statistical supremacy, a common-sense criteria for replacing pedagogical strategies and tools should be that the replacement be at least as effective with few, if any, subversive side-effects, when compared to its proposed predecessor (Daniel & Willingham, 2012;Gurung, 2017). For example, were we to find that less expensive electronic-textbooks were equivalent to more expensive print textbooks that would be a finding with tangible benefits. ...
... In fact, until equivalence criteria have been consistently demonstrated in representative contexts, we would urge all teachers to be skeptical of adopting the newest and shiniest methods, as it could TOWARD AN ECOLOGICAL SCIENCE OF TEACHING result in providing inferior, but less expensive, tools to our most vulnerable students, with potentially devastating consequences. For example, Gurung (2017) recently found that Open Educational Resource (OER) textbooks were less effective learning tools compared to publisher-provided textbooks, particularly for students with lower American College Testing (ACT) scores, a test administered to impending high school graduates designed to measure readiness for college or university, many coming from the exact lower-income population we are targeting a price-point argument. Without demonstrating equivalence to printed textbooks, the adoption of certain OER products potentially harms at least some students and subverts the efforts of good teachers. ...
Article
The need for a primary emphasis on teaching is a necessary, and as yet unfulfilled, goal of psychological science. We argue that an ecological model focused specifically upon understanding and optimizing teaching practice must incorporate the necessary complexity inherent to the teaching and learning process. To do so, we must expand our scope beyond the simple exploration of main effects under controlled conditions to the exploration of dynamic interactions, including the identifi- cation of boundary conditions, and the assessment of potential side-effects across relevant variables and contexts. To do so, foci on internal and external validity must be re-balanced in a manner more productive for practical inferences and applications. With an eye on educational practice, we point out that statistically insignificant results, under certain circumstances, can yield very useful strategies for teaching. Therefore, researchers interested in practical applications for teachers should be encouraged to use active control groups in their studies when feasible. We also argue that practical significance must include context-relevant information, for example, a ratio between the degree to which the findings can be used in context without upsetting other learning objectives and the amount of benefit given the costs (both time and energy) of the intervention, as an essential component to evaluating the potential utility of teaching research. Thus, statistically significant results must be weighed with respect to both effect-size and the practicality of implementation by teachers in authentic educational contexts before being considered a candidate for use in the classroom.
... Although these systematic analyses have concluded there is no overall difference in learning outcomes between OER and commercial resources, there is substantial variation in the findings. Some results indicate higher grades with OER compared to commercial textbooks (e.g., Colvard et al., 2018;Hilton et al., 2016), some a negative effect of OER (e.g., Gurung, 2017), and many show no statistically reliable difference between OER and commercial resources (Allen et al., 2015;Grissett & Huffman, 2019;Medley-Rath, 2018). The variation in findings did not appear to be driven by methodological issues such as whether prior academic achievement was controlled for or not or if the same assessment instruments were used in courses using OER and commercial resources (Clinton & Khan, 2019). ...
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Open educational resources (OER) are teaching and learning materials that are less expensive than commercial course materials. Previous findings have indicated that learning outcomes are similar between OER and commercial resources (which typically require fees to access), but there is considerable variation in the findings. It is not well known which students in what kinds of courses may have different outcomes with OER use. Two characteristics that are important to examine because they are becoming more commonplace in higher education and may struggle with social integration are nontraditionally-aged (age 25 and older) and online students. The purpose of this study is to examine how student age and course modality may vary how OER adoption relates to course grades, withdrawal, and number of credits enrolled in a given semester. To address this purpose, a dataset from seven public postsecondary institutions with 8,033 students was analyzed. Based on multilevel modeling findings, traditionally-aged students had higher grades with OER whereas OER did not reliably relate to the grades of nontraditionally-aged students. However, nontraditionally-aged students in face-to-face courses with OER had greater enrollment intensity (number of credits in a term). OER was not associated with withdrawal rate. Future directions are suggested, which include a need to consider instructor effects and directly hearing student voices on OER experiences.
... Students take a lot longer to read ebooks and are more likely to multitask than when reading traditional textbooks (Daniel & Woody, 2013). In addition, if students use an electronic version of an open educational resource (OER) text they do not perform as well on exams as do students assigned to traditional textbooks in either hard copy or electronic formats (Gurung, 2017). ...
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We exposed college students (N = 269; for 126, the first language spoken in the home was English) at a Hispanic-serving institution (HSI) to a passage from a digital psychology textbook in which input modality (reading or listening) and level of distraction were varied. Students did one of the following: read the passage, listened to the passage, read and listened simultaneously, listened while doodling (low distraction), listened while simulating a car ride (moderate distraction), or listened while preparing a meal (high distraction). We used a multiple-choice test to test recall. Student retention differed based on input modality. Specifically, conditions that removed text and replaced it with audio hindered performance. For example, students in conditions that involved reading the text showed higher recall scores compared to students in conditions that involved only listening (β = −2,483, p < .001). Performance worsened as we added distractors. Finally, the results suggest that students’ background with English is important for their retention of textbook information that is presented in English. Specifically, it appears that having text is more important to students less proficient in English than it is to more proficient English speakers. Our results suggest that reading digital texts leads to better recall than does simply listening to them, but distraction and early language experience may be important factors to consider when determining recommendations for digital textbook use.
... Although there is no denying the growth in OER collections and usage measured in baseline and longitudinal studies (de Oliveira-Neto, Pete, Daryono, & Cartmill, 2017;Seaman & Seaman, 2017), recent literature reviews are noting few studies on how OER relates to student-based measures such as learning, performance, engagement, and efficacy (Fischer, Hilton, Robinson, & Wiley, 2015;Grewe & Davis, 2017). In general, research and literature reviews and synthesis of the existing literature confirms equitable learning outcomes regardless of course resource cost (Bowen, Chingos, Lack, & Nygren, 2014;Hilton, 2016;Hilton, Gaudet, Clark, Robinson, & Wiley, 2013;Rockinson-Szapkiw, Courduff, Carter, & Bennett, 2013), although Gurung (2017) dissents with findings of lower student performance in courses deploying OER. In addition, several researchers found that OER adoption could serve as a modest predictor to students' completion of courses, class achievement, and enrolment intensity (Fischer et al., 2015;Law & Jelfs, 2016;Weller, De Los Arcos, Farrow, Pitt, & McAndrew, 2015). ...
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Evidence exists that American institutions of higher education are well-entrenched in the consideration of mechanisms for supporting the implementation of Open Educational Resources (OER) and alternative textbooks. Literature reveals that developing and implementing OER is a significant undertaking in terms of time and human resources. This study deploys content analysis of a sample of United States regionally based higher education institutional websites to determine the current state of institutional support mechanisms to implementers just embarking on the OER journey. Findings reveal that institutions have made strides in the development of faculty mini-grants and stipends with guidelines, proposal checklists, and weighting mechanisms to inform decision making. However, due to widespread language across the stratified sample emphasising award pool and individual limits, it is clear that OER funding is still seeking wider support as a permanent funded resource. Sponsorship of institutional OER initiatives seems split between institutional library functions and teaching and learning centres. Other issues, such as ownership and licensing, are significantly underdeveloped in field implementation or fall in a large continuum of practices. Recommendations of shared responsibility and use of data driven initiatives are provided that may improve institutional support of faculty OER adoption, adaption and creation.
... The impact of OERs on the educational experience of students and instructors has received recent attention in scholarly research. Studies have explored topics such as student and instructor perception of the quality of open and commercial textbook materials (Bliss, Robinson, Hilton, & Wiley, 2013;Brandle et al., 2019), barriers to the adoption of OERs (Seaman & Seaman, 2017, and student performance when using OERs compared to using commercial materials (Clinton, 2018;Gurung, 2017;Jhangiani, Dastur, Le Grand, & Penner, 2018). A 2016 meta-analysis of studies on the efficacy and perception of OERs reports that most studies show favorable perceptions of the quality and effectiveness of OER products from students and faculty (Hilton, 2016). ...
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Open educational resources (OERs) are materials that can be freely downloaded, edited, and shared to better serve all students. These resources are typically free of cost, reducing barriers to access for students and ensuring that all learners can have access to educational materials regardless of their financial status. OERs have been demonstrated to improve student performance and retention, especially for students traditionally underrepresented in higher education (e.g., first-generation, non-White students). Although there have been informal calls for additional OERs in behavior analysis, it is unclear whether behavior-analytic OERs exist. The aimof the current study was to use an OER aggregating metafinder to review what OERs are available on topics related to behavior analysis and whether sufficient resources exist to serve as primary course materials. Results indicate that OERs for behavior-analytic content exist but tend to be written by nonbehaviorists for use in survey courses in mainstream psychology. There also do not appear to be sufficient resources to support a course. Implications for promoting the development and dissemination of OERs, particularly with respect to increasing the recruitment and retention of diverse students in the field of behavior analysis, are discussed.
... Students report generating examples to help them learn concepts within their courses (Blasiman et al. 2017;Gurung et al. 2010;Weinstein et al. 2013). In a recent study, students reported spending almost 30 min generating examples in preparing for an upcoming exam (Gurung 2017). ...
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Declarative concepts (abstract concepts denoted by key terms and definitions) are foundational content in many courses at most grade levels. The current research compared the relative effectiveness of provided examples to faded examples (a technique involving a transition from studying provided examples to completing partial examples to generating examples) for learning declarative concepts. In two experiments (experiment 1: n = 146, experiment 2: n = 131), participants were randomly assigned to study provided examples or complete faded examples. Two days later, participants took two final tests to assess their long-term learning: a novel example classification test and an example generation test. Results across experiments were highly consistent: performance on both final tests was similar following provided examples and faded examples practice; however, provided examples took much less time to implement during practice. Therefore, considering both long-term learning and efficiency outcomes collectively for evaluating the effectiveness of learning techniques, provided examples continue to be more effective than techniques involving both provided examples and generated examples for learning declarative concepts.
... In contrast, Hilton and Laman (2012), Clinton (2018), Hardin et al. (2018), andJhangiani et al. (2018), found better outcomes for students using OER relative to those assigned commercial texts. To our knowledge, only one study found that students who used OER performed worse (on an AP Psychology exam) than those using a commercial textbook (Gurung, 2017). ...
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A college education is becoming increasingly expensive, and the burden of this cost is often felt disproportionately by marginalized students. One aspect of rising college costs are textbook prices, which have increased at a rate that far surpasses inflation. Open educational resources (OER; free, openly-licensed course materials) are often proposed as a solution to this problem. It is not clear, however, whether these materials are equivalent in quality to standard commercial textbooks. During one semester, half of the Introductory Psychology sections at a large, public university were assigned to use OER while the other half were assigned to use the incumbent commercial textbook. Participants were asked to self-report the behaviors they engage in as a result of high textbook costs. We also examined student performance in the courses and students' perceptions and use of the two books. We found no significant differences between textbook groups on course performance or perceptions of the book, but marginalized students (first-generation students and/or ethnic minority students) reported engaging in negative behaviors (i.e., dropping a class) more often than their peers as a result of textbook costs. These findings suggest that textbook costs disproportionately affect our most vulnerable students and the use of OER may be one solution to this problem, particularly given the equivalent performance across textbook groups.
... While some OERs undergo a review and editing process similar to that of commercially produced textbooks (e.g., OpenStax, Noba), practices are inconsistent. Despite the differences between OERs and commercially-produced textbooks used in psychology courses, students typically report similar use and perceptions of these two resources (reviewed in Clinton, 2019), although data about performance in courses using OERs is less clear, in part, due to variations in how performance is assessed (e.g., Gurung, 2017;Hilton & Laman, 2012). Taken together, these findings suggest that the replacement of a commercially produced psychology textbook with an OER textbook is a money saving solution that is unlikely to negatively impact the educational experience of students. ...
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The high cost of college textbooks is an access barrier for students to overcome during their pursuit of a college degree. Perhaps most at risk are community college students, an older, more diverse, lower-income population in comparison with their university peers. Recently, community colleges have considered replacing traditional, commercially-produced textbooks with free open educational resources (OERs). In this work, two aims were addressed. First, a small-scale investigation of the need for a low-cost textbook alternative was conducted in an introductory psychology course. In response to the finding that over a quarter of students could not afford the course textbook, a psychology OER was adapted from existing resources and piloted in three sections of this course. The second aim was to assess the impact of this OER textbook. Findings from this second survey found that the psychology OER was easy to use, high quality, and supported students in their understanding of course content. Students also reported that the money saved from not having to buy a textbook made taking the course easier. Together, these findings support that OER textbooks are suitable replacements that can reduce the financial burden on low-income students and support them in the achievement of their academic goals.
... Few existing OER impact studies can plausibly address this question. While several studies have attempted to control for student variables using quasiexperimental statistical designs (Gurung, 2017;Clinton, 2018;Jhangiani et al., 2018;Venegas Muggli and Westermann, 2019), these studies did not evaluate whether the effects of OER were different for demographic groups that may be more likely to have issues accessing commercial textbooks. By contrast, Colvard et al. (2018) predicted that "students from low socioeconomic backgrounds that require substantial financial assistance to attend college would exceedingly benefit from courses that have adopted a free textbook when compared to previous semesters when traditional, commercial textbooks were used." ...
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This article examines the impact of Zero Cost Textbooks (ZCB) courses on two key factors of students success: pass rates and completion rates. We examine 3 years of data at Houston Community College, ending with the first year of their implementation of a ZCB program. Following the “access hypothesis,” we suppose that students who would not otherwise be able to purchase traditional textbooks will have higher pass rates and completion rates in ZCB courses. We use Pell recipient status and ethnicity as proxies for socio-economically disadvantaged students, targeting those populations where the access hypothesis will have the greatest impact. We isolate faculty who taught both ZCB and non-ZCB courses during the period under review and conduct a post-hoc analysis, using mixed effects logistic regression, to identify interactions between student and course characteristics and success metrics. We find that HCC's ZCB program had a statistically significant positive effect on pass rates for all students, but no effect on completion. We find a trend to suggest the ZCB program may improve success among Black students, but only a statistically significant positive effect among Asian students, and no interaction with Pell recipient status. These results are not well-explained by the access hypothesis; they suggest the need for further research.
... To learn more about the perceptions of faculty toward OER on college campuses, many libraries turn to institutional surveys. In a meta-analysis of some OER perception studies, Hilton (2019) identified two major trends: first, although the use of OER does not have a strong, direct impact on student learning, OER do not harm student learning either (Croteau, 2017;Lawrence & Lester, 2018;Winitzky-Stephens & Pickavance, 2017); and second, a majority of faculty and student surveys have positive opinions on the use of OER in their courses, even when compared to commercial textbooks (Gurung, 2017;Ikahihifo et al., 2017;Jhangiani et al., 2018). ...
... Machine learning may be suspected of infringement of technical measures or violations of laws and regulations, which can independently determine learning objects, construct their characteristics, perform additional operations beyond the limitations of preset instructions, and discover value from the expression of works [4]. e original material for machine learning is data, and how to deal with the rights above data, such as the right to privacy, personal information, and trade secrets, is a major legal issue facing the development of artificial intelligence technology [5]. e rule management of intellectual property rights protection can test not only the correlation between the characteristic variables and the data quality of intellectual property education resources but also the importance of the characteristic variables to the data quality of intellectual property education resources. ...
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Educational resource data are a collection of final documents obtained by users, including full-text journals, books, dissertations, newspapers, conference papers, and other database materials. While searching for information in the educational resource database, these resources also have functions such as copying, downloading, reproduction, and dissemination, which raise the issue of expression and protection of intellectual property. Machine learning takes how computers simulate human learning behaviors as the main research content, which can independently determine learning objects, construct their characteristics, perform additional operations beyond the limitations of preset instructions, and discover value from the expression of relative works. On the basis of summarizing and analyzing previous research works, this paper expounded the current research status and significance of intellectual property expression and protection of educational resource data; elaborated the development background, current status, and future challenges of machine learning technology; introduced the methods and principles of data classification algorithm and protection authority identification; performed the technical framework design and expression system establishment of the intellectual property expression of educational resource data based on machine learning; analyzed the mode optimization and rule management of intellectual property protection of educational resource data based on machine learning; and finally conducted a simulation experiment and its result analysis. The results show that the machine learning technology can build a subject-oriented, highly integrated, and time-changing educational resource data storage environment; the comprehensive, analysis-oriented decision-supporting system formed by machine learning can give full play to the potential role of data integration and value discovery and is therefore of great significance for the intellectual property expression and protection of integrated and complexly-related educational resource data. The study results of this paper provide a reference for further research on the intellectual property expression and protection of educational resource data based on machine learning. 1. Introduction Educational resource data are a collection of final documents obtained by users, including full-text journals, books, dissertations, newspapers, conference papers, and other database materials. In the data expression and protection of intellectual property educational resources, many documents are collected in commercial databases with the right to use, and the resources in the library are searched, downloaded, and integrated into characteristic databases [1]. These resources also have copying, downloading, copying, dissemination, and other functions, which caused intellectual property issues. According to different types of educational resources, machine learning educational resource data can be divided into government educational resource data, other public institution educational resource data, corporate educational resource data, and personal educational resource data [2]. The mode optimization can generate massive amounts of data in real time and process them in real time to ensure that intellectual property education resource data become a handy resource anytime and anywhere. In the machine learning environment, educational secret data may not be lost due to the protection of a data backup system, but educational resources may lose control of educational secret data due to data migration obstacles [3]. Machine learning may be suspected of infringement of technical measures or violations of laws and regulations, which can independently determine learning objects, construct their characteristics, perform additional operations beyond the limitations of preset instructions, and discover value from the expression of works [4]. The original material for machine learning is data, and how to deal with the rights above data, such as the right to privacy, personal information, and trade secrets, is a major legal issue facing the development of artificial intelligence technology [5]. The rule management of intellectual property rights protection can test not only the correlation between the characteristic variables and the data quality of intellectual property education resources but also the importance of the characteristic variables to the data quality of intellectual property education resources. The strict regulation and improvement of the liability clause, dispute settlement clause, and confidentiality clause of the license agreement can ensure that the work is copied and disseminated under reasonable use purposes, thereby restricting the dissemination and scope of the data work and preventing illegal use, so that the legitimate rights and interests of the right owner of the data work will not be harmed and machine learning is a science of artificial intelligence [6]. Algorithms mainly including decision trees, support vector machines, neural networks, genetic algorithms, and machine learning technology are a key link in data mining and data protection [7]. The intellectual property expression and protection of educational resource data must be established on the basis of technological innovation in order to implement the concept of public welfare, expression, and protection of knowledge [8]. On the basis of summarizing and analyzing previous research works, this paper expounded the current research status and significance of intellectual property expression and protection of educational resource data, elaborated the development background, current status and future challenges of machine learning technology, introduced the methods and principles of data classification algorithm and protection authority identification, performed the technical framework design and expression system establishment of the intellectual property expression of educational resource data based on machine learning, analyzed the mode optimization and rule management of intellectual property protection of educational resource data based on machine learning, and finally conducted a simulation experiment and its result analysis. The study results of this paper provide a reference for further researches on the intellectual property expression and protection of educational resource data based on machine learning. The detailed chapter arrangement is as follows: Section 2 introduces the methods and principles of data classification algorithm and protection authority identification; Section 3 performs the technical framework design and expression system establishment of the intellectual property expression of educational resource data; Section 4 analyzes the mode optimization and rule management of intellectual property protection of educational resource data; Section 5 conducts a simulation experiment and its result analysis; Section 6 is the conclusion. 2. Methods and Principles 2.1. Data Classification Algorithm Intellectual property education resource data constitute two important data sets in data mining: training data and test data. In terms of content selection, the possibility of intellectual property protection is inversely proportional to the breadth of data and information; that is, the more comprehensive the collection of data and information is, the less selective it is and the less its originality in the selection of content. The comprehensiveness of the data information content is exactly where its educational value lies. The consistency of educational resource data refers to the consistency of the distribution of data in different domains. Suppose n different fields X = {x1, x2, …, xn} and the number of resources in each field is {y1, y2, …, yn}, then the educational resource data consistency y (xi) of the candidate data xi is defined aswhere f (xi) is the number of expressions of candidate data appearing in resource xi. When the candidate data f (xi) is more evenly distributed in each resource of the intellectual property, the consistency of the educational resource data y (xi) is also greater, indicating that it is likely to be filtered data. When the computer uses the training set to train the model, overfitting may occur; that is, the training sample reaches very high approximation accuracy, but the approximation error of the test sample first decreases and then rises with the number of training times. The random forest model will use the exponential gain Q (xi) as the basis for the selection of the decision tree:where a (xi) is the proportion of the number of samples of category xi in all samples; b (xi) is the decision tree judgment node of the samples of category xi; c (xi) is the number of split points of samples of category xi; and d (xi) is the category xi of the number of samples in all samples. For machine learning, it is easy by changing the protection structure of data information to circumvent copyright protection, which will make the protection of data information meaningless. The value and significance of data information lies in the information material itself rather than the structural order of the information material. The structure that loses the content of the information is just an empty shelf without a soul, with little protection value at all. Therefore, even for original data information, the principle of only protecting expressions but not protecting ideas makes the protection of data information still very weak. The weighted average of the expression difference ratio of the candidate educational resource data is used in the field of intellectual property, and a comprehensive index to filter the infringement data in the resource data set is defined as follows:where e (xi) and are respectively the total number of expressions of resource data xi in the intellectual property field; h (xi) and k (xi) are the respective contributions of the intensity and expression difference ratio of data resources xi; and l (xi) and m (xi) indicate the frequency of expression and protection of candidate data resources xi in the field of intellectual property. As a result, data information that does not have originality is a ubiquitous thing and will increase greatly with the development of the information service industry, but intellectual property cannot provide corresponding protection for data information that does not have originality. According to the principle that machine learning only protects expressions but not ideas, what intellectual property protects of data and information is its original choice or protected expression, not the content it chooses or protects. 2.2. Protection Authority Identification The intellectual property expression and protection of educational resource data refer to the whole process of resource data collection, input, processing, analysis, regeneration, and output. At present, many intellectual property education resource data management systems reflect the expression and protection of some resource data. Through the realization of data expression and protection, the informatization, intellectualization, and even decision-making management of intellectual property education resource data can be completed. The average expression probability of educational resource data xi in a single intellectual property indicates the intensity of xi in the resource field, so the intensity E (xi) of resource data xi can be expressed aswhere o (xi) is the frequency of expression of educational resource data xi in the entire intellectual property; and p (xi) is the number of expressions of resource data xi in the field of intellectual property. In addition, how to use data warehouse technology to build a subject-oriented, highly integrated, stable, and time-changing data storage environment to form a comprehensive, analysis-oriented decision support environment has become an urgent issue for data integration of intellectual property education resources. Another important question is related to the integral educational resources, which reflects the complex correlation between intellectual property education resource data, similar to the intertwined network of relationships. The time domain analysis method is to express the information distribution of the educational resource data xi as a function of time; the frequency domain analysis method is to obtain the frequency domain and its energy frequency domain distribution through the transformation of the educational resource field, so the transformation of the educational resource data T (xi) iswhere ai is the expression range factor; bi is the protection efficiency factor; and ci is the total number of data to be protected. The intellectual property expression of educational resource data includes two steps: one is to establish a statistical model through the identification and calculation of the classification of the training set flow; the other is to apply the established statistical model to the unknown and new flow classification in the network traffic. So the probability that each educational resource data belongs to a specific application iswhere q (xi) is the prior probability of educational resource data xi; r (xi) is the conditional probability of given educational resource data xi; s (xi) is the number of times the educational resource data xi performs information automation; and t (xi) is the total number of times of information processing of educational resource data xi. This method assumes that the characteristics of educational resource data are independent of each other. From an overall point of view, the competent information department takes charge of the overall situation and integrates all business systems. Based on the classification of intellectual property education resource data, data expression and protection will realize the standardization and distributed management of data and ensure the smooth flow of data. Partially, the administrative and teaching departments of universities will be responsible for the management of specific educational resource data, and data expression and protection will realize the specific business of each department. 3. Intellectual Property Expression of Educational Resource Data Based on Machine Learning 3.1. Technical Framework Design Educational resource data types include not only structured data, but also a large amount of semistructured data and unstructured data, and structured data refer to data with a fixed format and limited length. Unstructured data refer to data with variable length and no fixed format. Data expression and products of educational resources based on machine learning are usually protected by copyright in the early days, but copyright protects the expression form of ideas, the data expression and the selection, arrangement, system, and structure of the work, rather than the protection of the data itself [9]. And if the data are provided in the form of public dissemination, it will inevitably be exposed to and obtained by an unspecified number of people, and the service provider cannot guarantee that its application purpose must comply with the rules, which creates the risk of copyright infringement. Therefore, the data work operator should establish a reasonable control method, use one-to-one network transmission, and protect the security of the data work in terms of identity authentication, access permission control, and control of the operating environment, so as to effectively prevent piracy, illegality, and the occurrence of copying behavior. In this case, the license agreement for the data work becomes a legally binding agreement between the user and the data operator regarding the purchase of the copyright license for the data work. Figure 1 shows the framework for intellectual property expression and protection of educational resource data based on machine learning.
... However, the lack of random assignment in quasi-experiments limits the likelihood the compared groups were similar in important characteristics such as demographics or prior academic achievement. For these reasons, Clinton's review of OER in psychology courses (2019) called for better control of potential confounds as this lack of control is a valid critique of OER efficacy research (see Griggs & Jackson, 2017;Gurung, 2017). Indeed, Clinton (2018) found that differences in prior academic achievement likely explained differences in learning outcomes when comparing an introduction to psychology course with a traditional textbook to one with an OER textbook. ...
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... The material covers the diversity of invertebrates, mostly discussed in the form of reading displaying neither attractive nor colorful pictured examples making students less interested in reading and studying them. According to Gurung (2017), students tend to enjoy reading textbooks if it is provided with lots of colorful pictures with few descriptions. Images can increase reading interest because they can help readers imagine. ...
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The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique? 2a. Learning conditions 2b. Student characteristics 2c. Materials 2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students’ performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self-explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique. Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading. These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness. The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students’ performance, so other techniques should be used in their place (e.g., practice testing instead of rereading). Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research.
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