Abstract
There is a considerable gap between many of the findings from educational psychology research and educational practice. This gap is especially notable in the field of science education. In this article, the implications of three categories of research and their findings for science educational policy in the USA and other jurisdictions were reviewed. We indicate that a particular category of research that we call “Program-Based Studies,” has dominated the formulation of educational standards while a large number of critical findings from randomized, controlled studies and correlational studies that overwhelmingly show minimal support for the suggested policy have been marked as irrelevant and excluded. The current blanket-emphasis on program-based studies at the expense of the other types of research is misplaced. Educational standards should represent a balanced view of the available data including findings from controlled and correlational studies. Finally, we indicate how these different forms of research might inform each other and provide coherent and consistent implications for educational procedures.
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Introduction
Educational psychology has the potential to provide findings to inform a variety of educational teaching and learning decisions and practices. That potential is frequently but not always realized. We identify a disconnect between educational suggestions made by extensive bodies of educational psychology research findings and common educational practices promoting inquiry and exploration as a pedagogy. A lack of discussion on various categories of research findings and their different implications for educational practice has contributed to this disconnect, leading in turn, to an evidence crisis with adverse consequences for the formulation of educational policy. We unfold this evidence crisis in science education as it is a heavily researched field with a broad cross sample of research methodologies. More importantly, the exploration-based pedagogy, frequently called “inquiry,” “discovery,” “problem-based,” or “investigations,” has been prominently reflected in science education practice and policy for decades in the USA and internationally.
The emphasis on incorporating scientific investigation in science curricula has been a global phenomenon and is commonplace. A few examples are as follows: In Australia, ACARA (Australian Curriculum Assessment and Reporting Authority, 2018) revised and released its Year 10 Australian Curriculum to emphasize students’ involvement in scientific inquiry methods to conduct investigations. More recently, new draft versions of policies in all school curricula areas were released for comment and feedback and are currently under revision after considerable public controversy over the emphasis on inquiry-based learning. In the Netherlands, curriculum reforms, such as Our Education2032 (Platform Onderwijs, 2032, 2016) and, more recently, curriculum.now (Coördinatiegroep curriculum.nu, 2019) have focused primarily on emphasizing inquiry learning. Similarly, in Canada, a curriculum was restructured around an inquiry process model to encourage students to ask and pursue questions through scientific explorations and investigations (British Columbia Ministry of Education, 2015). As part of the global community, science education in the USA has played an important role in advocating the integration of investigations into science teaching and in leading curriculum reforms worldwide. This emphasis is disconnected from some very common forms of research, namely randomized controlled studies and correlational studies. Such a disconnect is inevitably noticeable in the field of science education and has led to consequences in the formation of educational policy world-wide. We will focus the rest of our discussion on the USA.
In the early 1960s, American educators responded to the Soviet Union’s Sputnik launch—rarely mentioned today (Kirschner, 2000)—embracing the assumption that the best way to educate young “scientists” was to use the epistemology of the expert scientists (Kirschner, 1992). Investigations, usually conducted in science laboratories but also used as a more general instructional/pedagogical classroom technique, were introduced to provide learners with opportunities to come up with their own understanding of the discipline through experimentation. For example, scientific inquiry was promoted in the 1996 National Science Education Standards (NSES) as an instructional approach and science teaching shifted from directly providing students with established content to having them go through a scientific inquiry process, including formulating research questions, making observations, collecting and analyzing data, and drawing conclusions (National Research Council, 1996).
In the years that followed, some categories of evidence supporting this approach became available, including attempts to improve students’ understandings of science concepts, develop ownership of the knowledge, foster positive attitudes toward science, and promote practical skills in authentic settings (Barton & Tan, 2010; Edelson & Reiser, 2006; Geier et al., 2008; Mistler-Jackson & Songer, 2000; Shaffer, 2004; Songer et al., 2002, 2003; Williams & Linn, 2002). Much of this evidence was from field-initiated projects and programs grounded in a category of research we have called ‘Program-Based Studies’ (see below).
The Next Generation Science Standards (NGSS) (NGSS Lead States, 2013) is the most recent American effort at developing national science standards, and in these standards “inquiry” as a process has been replaced by “scientific practice.” Scientific investigation continues to be emphasized, but characterized as scientists practicing the science profession to discover the unknown. It is clear that the newly developed standards intend to further integrate the development of scientific ideas with the engagement of scientific practice, as articulated in the Framework for the NGSS (National Research Council, 2012, p. x in Foreword Section), and argue that both are essential to science learning. These arguments, as in the 1996 NRC NSES, emphasize that science learning goes beyond science content and that there is a much broader set of outcomes for science education in this new century, from strengthening a deeper understanding of science, developing a greater interest in and appreciation of science, to promoting higher scientific skills and competency to enter careers, to foster social communications, and to deal with this ever-changing world. It is also worth mentioning that even a quarter of a century ago, Hodson (1996) summarized and debated this same set of arguments used by educators for developing a broader set of science education learning outcomes. The issues are perennial.
Indeed, the rapidly evolving world requires education to carefully provide and prepare future citizens with the knowledge and skills that they will need. Educational standards need to set clear expectations and guide educators with a detailed plan to achieve them. We have no objections to standards documents that provide expected learning outcomes. We are concerned however, that while it is appropriate for standards to provide outcome expectations, the current standards also promote certain instructional approaches for achieving these expectations and that the suggested approaches are based almost exclusively on only one category of research, namely program-based studies, neglecting other research categories.
For example, as a way to integrate three dimensions (science and engineering practices, science disciplinary core ideas, and crosscutting concepts), the standards often suggest that students “plan and conduct investigations to determine…” (NGSS Lead States, 2013, 1-PS4-3. & 2-LS2-1.) where the core outcomes are treated as a likely or even inevitable product of the investigation process. The Framework that is used to philosophically and empirically guide the development of the NGSS states that “Core ideas in the framework are specified not as explanations to be consumed by learners…The practices include several methods for generating and using evidence to develop, refine, and apply scientific explanations to construct accounts of scientific phenomena…The expectation is that students generate and interpret evidence and develop explanations of the natural world through sustained investigations” (National Research Council, 2012, pp. 254–255). There is no suggestion provided in those documents that these goals might be better reached, at least under some circumstances, by procedures other than investigations, such as “explanations to be consumed by learners.”
We are concerned that while NGSS provides appropriately clear learning outcome expectations, it is also committed to teaching science core ideas by having students achieve them primarily, if not exclusively, by going through investigation steps as an exploration process where the answers to the investigations are not presented to students, but obtained during the investigation process. We argue that although the terms used to characterize the scientific process have been changed over the years from “inquiry” to “scientific practice,” their emphasis on teaching science through investigations has remained and their characterization of the investigation procedure as an instructional/pedagogical approach is the common ground shared between the 1996 and 2013 standards.
Science education scholars such as García-Carmona (2020) noted that these two sets of standards are almost identical in terms of their promoting scientific process in science instruction and argued that the elements used to characterize the activities undertaken by scientists were not substantially different in the NGSS from the previously promoted inquiry approach of the 1996 standards. We are concerned that the same rationale is reinforced to justify a need for this newly named but pedagogically identical approach to science teaching while psychologically oriented studies that often isolate factors in controlled conditions to identify causal effects are marked as “simplistic,” even “mistaken,” and are systematically excluded (National Research Council, 2012, p. 253). We emphasize that a series of differently named instructional strategies, including problem-based learning, discovery learning, inquiry-based learning, exploration-based investigation, all withhold some direct, explicit instruction and replace it with different forms of problem solving and that they have dominated the way that scientific investigations are characterized in science instruction. As a result, there is a limited view of how scientific investigations should be integrated into science teaching to develop scientific ideas and skills. The field has been heading in an inquiry learning/investigations direction over decades while ignoring a considerable body of psychologically oriented findings that speak directly to the pedagogical principles shared among all these differently named strategies.
We never should have reached the current point, as accumulated evidence from controlled studies, on which the field of educational psychology relies heavily, has found minimal support for teaching science through exploration-based investigations. For example, controlled studies compared the aforementioned inquiry- or exploration-based investigation approach to science teaching with various forms of explicit instruction, such as simply providing students with the desired information and having students read it from texts or watch demonstrations. Overwhelmingly, these studies supported the suggestion that students demonstrated greater learning of the content from the various forms of explicit instruction (Ashman et al., 2020; Hsu et al., 2015; Klahr & Nigam, 2004; Matlen & Klahr, 2013; Renken & Nunez, 2010; Stull & Mayer, 2007; Zhang, 2018, 2019). It should be noted that many of these studies were not carried out in a psychological laboratory, but used real classrooms with students studying relevant curriculum materials.
Supporting the findings from controlled studies, an entirely different category of research, correlational studies, have used large data sets, such as TIMSS (Trends in International Mathematics and Science Study) and PISA (Program for International Student Assessment), to examine the effectiveness of an investigation approach to science teaching over large populations. Consistently, these studies across years and countries found that the more students were involved in exploration-based investigations, the lower was their performance (Aditomo & Klieme, 2020; Areepattamannil, 2012; Cairns & Areepattamannil, 2019; Forbes et al., 2020; Gao et al., 2017; Jerrim et al., 2019; Kaya & Rice, 2010; Lavonen & Laaksonen, 2009; Liou, 2020; McConney et al., 2014; Zhang & Li, 2019). Reviewing this accumulated evidence, we are left to ponder how research evidence has been selected to develop suggestions for educational policies, such as the NGSS.
The divergence of views has been debated by many scholars (Hmelo-Silver et al., 2007; Kuhn, 2007; Lee & Anderson, 2013; Matlen & Klahr, 2013; Schmidt et al., 2007; Sweller et al., 2007; Tobias & Duffy, 2009; Zhang, 2016). The NGSS was developed in 2013, several years after the initial papers from these debates were published, but nevertheless, promoting the same incorporation of investigations in science teaching and addressing none of the issues and concerns raised in the debate. Currently, a new report has been published with a call to action (National Academies of Sciences, Engineering, and Medicine, 2021) which addresses critical issues in science education but employs the same way of characterizing investigations in science instruction as in the past, despite all prior efforts. We acknowledge the complexity of the issues but are concerned that policy documents are ignoring findings unfavorable to inquiry-based approaches and that they are automatically assumed to be irrelevant. As the field continues to grow, inevitably more examples of findings incompatible with current procedures will emerge. Those incompatibilities should be discussed and if possible, resolved.
In the following, we unfold the disconnections between different forms of research and their suggestions for science education. To be clear and specific about the issues we intend to present here, we focus our debate on contradictory suggestions made for enhancing students’ learning of science concepts and procedures. We believe that science conceptual and procedural understandings are indispensable to the high-level learning of any science topics. As noted earlier, we have no objections to the various science learning outcomes that are strived for. Nor do we reject any data indicating that investigation activities can be included to achieve different learning goals. We argue however, that:
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The development of students’ science conceptual knowledge is not best obtained by having students go through exploration-based investigation activities.
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Although we hold that scientific procedures are an essential part of science education, we do not believe that investigative skills and methods in specific science fields emerge automatically as students engage in such investigation activities. Rather, they need to be explicitly and directly taught and then sufficiently practiced in guided or open situations. We are also aware that the current standards tend to emphasize the development of a generic set of inquiry/problem-solving skills covering several science subject fields. The expectation is that once students acquire these so-called general problem-solving skills in their early education they will be able to perform better in specific fields when they launch their careers in future. While the acquisition of such skills is debatable, there can be no doubt that for students to be able to successfully carry out scientific investigations, they need to acquire conceptual and procedural content.
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The development of other related science learning goals during investigation activities, such as attitudes toward science, should not be at the cost of students’ learning of science concepts and procedures.
We suggest that the disjoint between policy documents and research evidence is exacerbated by the tendency to ignore categories of research that do not provide the favored research outcomes that support teaching science through inquiry and investigations. We also indicate how different forms of research might inform and strengthen each other during interdisciplinary collaborations to provide coherent and consistent implications for educational practice. Finally, we discuss the barriers to arriving at research-based conclusions.
Disconnections Between Various Forms of Research and Their Different Implications
In this section, we describe three different categories of research, namely program-based studies, randomized controlled studies, and correlational studies. We point out that program-based studies have yielded different results from the other two categories.
Program-Based Studies
Integrating scientific investigation steps into science teaching has been the focus of science educational reforms for decades. As we have already noted, the 1996 NRC NSES promoted an inquiry-based approach to science teaching and claimed that “engaging students in inquiry helps students develop understanding of scientific concepts, an appreciation of ‘how we know’ what we know in science, understanding of the nature of science, skills necessary to become independent inquirers about the natural world, and the dispositions to use the skills, abilities, and attitudes associated with science” (National Research Council, 1996, p. 105). A major problem with the NSES is that the references it used to support these claims and standards were more theoretical ideas packaged in conceptual articles rather than empirical evidence.
Following the 1996 NRC science educational standards, there were nation-wide, sweeping curriculum reform efforts. Many centers and programs were funded and built to promote inquiry-based science teaching and program-based studies were prevalent. We highlight this type of study as a key category for discussion because such work has been representative, indeed dominant, in driving educational practice.
This type of study does use quantitative data to measure the effectiveness of a program. In addition, qualitative data are also incorporated to provide detailed descriptions of students’ learning experiences in the program. Among many of these studies, a pre-post research design was often used. For example, the Kids as Global Scientists (KGS) program was funded and built using scientific inquiry as its overarching instructional approach. By comparing students’ pre-post performance, the research team found that participating students significantly improved their understandings of science content and inquiry skills (Songer et al., 2002). Qualitative data, like classroom observations and teacher interviews, were also collected to provide examples of classroom teaching. No doubt, these researchers built a rigorous science learning program and brought quality learning experiences to students. Nevertheless, the positive results obtained using this research design without, for example, a proper control group, may only reflect the effectiveness of the program in terms of its capability in achieving desired student learning outcomes. It does not provide evidence for the effectiveness of inquiry-based instructional approaches over other methods due to its lack of comparisons with a control group or other teaching approaches. The authors themselves stated, “this study was not intended to demonstrate the effectiveness of the KGS intervention on student learning as compared to other interventions or traditional teaching methods” (Songer et al., 2002, p. 137). We share that view.
Program-based studies frequently also use research designs that compared student learning outcomes in the treatment group with those receiving “business as usual” as a way to evaluate the impact of a program. These programs often incorporate many instructional elements, from various forms of technology support to intensive teachers’ professional development workshops. Thus, it is questionable that students’ learning gains can be attributed only to the use of an inquiry-based approach, rather than other factors these programs also implement. For example, the Center for Learning Technologies in Urban Schools (LeTUS) is another inquiry-based learning program built during that period. The research team compared LeTUS participants’ learning outcome with those who did not participate and found that students enrolled in LeTUS inquiry-based science curricula performed significantly better (Geier et al., 2008). Nevertheless, because this program built in various instructional elements (e.g., the technologies used, the teacher training employed, the extra resources provided), the favorable findings capture only the impact of this program as a whole over the counterpart and cannot support the claim that students’ outstanding performance was caused by the inquiry-based approach used.
For the above reasons, we emphasize that there are differences between studies that examine inquiry as an instructional approach by separating out other contaminating factors and studies that vary levels of inquiry simultaneously with many other elements. Program-based studies are often conducted by educational researchers to compare the relative efficacy of an entire program or a curriculum over others. Such studies are important and that importance should be reflected in policy documents but the effectiveness of a program should not be attributed to any one of the designed specifics. It is not possible to derive conclusions concerning the efficacy of inquiry-based procedures (or for that matter any other procedure thus implemented) compared to more explicit instruction without at least some studies using a strict control of variables. Unfortunately, the main source of evidence in the field of science education about inquiry-based teaching comes from studies that more or less share the key characteristics discussed above. In a review of research on inquiry-based science instruction conducted between 1984 and 2002, Minner et al. (2010) found that out of the 138 studies from the final review list, 53% did not have a comparison group and about another 25% used non-equivalent control groups. Their review indicated that many instructional components were included simultaneously when examining the impact of inquiry interventions and the levels of inquiry components included in the interventions varied substantially. Accordingly, the vast majority of studies examining inquiry-based science instruction are unable to serve as evidence supporting inquiry as an instructional approach.
Based on this work, it seems to us that the assumption that inquiry as an instructional approach improves students’ learning has not been seriously tested since it was suggested decades ago as a theoretical idea. In 2002, Hofstein and Lunetta (2004) revisited their 1982 review (Hofstein & Lunetta, 1982) of research on inquiry-based laboratory science teaching. They stated in their 2002 review (published in 2004), “researchers have not comprehensively examined the effects of laboratory instruction on student learning and growth in contrast to other modes of instruction, and there is insufficient data to confirm or reject convincingly many of the statements that have been made about the importance and the effects of laboratory teaching” (p. 29). Twenty years later, in their 2002 review, these scholars stated, “…these comments are also valid at this writing 20 years later. That said, the assumption that laboratory experiences help students understand materials, phenomena, concepts, models, and relationships, almost independent of the nature of the laboratory experience, continues to be widespread in spite of sparse data from carefully designed and conducted studies” (p. 46). Today, almost another 20 years later, these researchers’ concerns continue to echo. The use of inquiry learning as an instructional approach has been normalized on the assumption that the data overwhelmingly support that use. Many programs and curricula have been built using inquiry as an overarching instructional framework. Claims from field-initiated, program-based studies continue to be widely used as evidence to further promote inquiry approaches. An effective program does not indicate the effectiveness of any specific instructional approach, such as inquiry, that occurs within a program with many other elements. We need at least some studies demonstrating the advantages of inquiry-based learning over other approaches, using strict, randomized, controlled trials. Such controlled studies are widely available in the field of educational psychology but are frequently ignored when informing educational practice.
Controlled Studies
Controlled studies use comparison groups and design intervention units that alter only one target factor at a time to examine the effectiveness of an instructional procedure over alternatives. This type of study commonly uses random assignment to ensure equivalent groups (within the bounds of probability) as opposed to matching. Because this type of study does not intend to examine the effectiveness of an entire program as a whole, it often does not design exemplar curricula or programs to simultaneously include all suggested instructional elements, such as technologies and teacher professional development, for testing. Rather, the intervention design focuses only on one target procedure at a time over alternatives. It needs to be emphasized that interactions between factors can be and are often tested using factorial designs that simultaneously indicate the effect of two or more single factors and the interactions between them. The important point to note is that these studies allow assessment of the relative effectiveness of a single factor such as inquiry-based teaching as an instructional approach over other approaches.
With replications of experiments, it is possible to provide recommendations with considerable confidence (Mayer, 2003; Slavin, 2002). Whitehurst (2002, 2003), the then-director of Institute of Education Sciences (IES), argued that all evidence is not created equal and listed randomized, controlled trials as the “gold standard” for determining the effectiveness of instructional approaches. When faced with uncertainty concerning the effectiveness of competing approaches, Shavelson and Towne (2002) stated “ [a] control group that has the same experiences as the experimental group except for the “treatment” under study is the best antidote” (p. 69). For these reasons, studies from the field of educational psychology heavily rely on this form of research to make instructional decisions.
Controlled studies have compared teaching involving exploration-based investigations with forms of direct explicit instruction, including simply giving students answers, having students watch demonstrations and listen to explanations, directly reading answers from texts, etc. These studies found that learners receiving these forms of direct, explicit instruction demonstrated greater learning of content and skills than those who learned through practicing investigations (Hsu et al., 2015; Klahr & Nigam, 2004; Matlen & Klahr, 2013; Renken & Nunez, 2010; Stull & Mayer, 2007; Zhang, 2018, 2019). A comprehensive analysis of 72 intervention studies examining students’ learning how to control variables during investigations (Schwichow et al., 2016) concluded that there is no evidence supporting the claim that teaching through inquiry-based, exploration-type investigations leads to better learning. Another comprehensive review of inquiry-based instruction by Lazonder and Harmsen (2016) concluded that students’ learning gain did not result from completing learning tasks by acting as scientists, but derived from direct explanations added to the program, which is clearly contradictory to the suggestion made in the Framework of the NGSS that “Core ideas…are specified not as explanations to be consumed by learners…” (National Research Council, 2012, p. 254). This trend is not surprising because there is a considerable number of findings using psychology of learning theories in favor of direct, explicit instruction when comparing it with exploration-based learning (Carlson et al., 1992; Kyun et al., 2013; Mayer, 2004; Moreno, 2004; Rittle-Johnson, 2006; Roussel et al., 2017; Tuovinen & Sweller, 1999). Evidence for the importance of direct, explicit instruction from a very large number of randomized, controlled studies suggests that for novice learners in a complex area, studying worked examples demonstrating the solutions of those problems has usually resulted in superior performance over conventionally used classroom practices finding the solution to the equivalent problems (Sweller et al., 2011, 2019).
There are various misunderstandings about the principles guiding controlled studies and their contributions to the field. The result is that a considerable number of such studies in educational psychology, like the ones listed above, have been left unattended in the formulation of science educational standards. Some argue that this type of study views instructional approaches dichotomously as either direct instruction or inquiry and is too simplistic to fully represent real classroom learning. We reiterate that this type of study is not intended to provide exemplar curricula. Rather, they exclude contaminating elements to focus only on target procedures or factors over alternatives. The objection to scientifically rigorous experimental design is particularly ironical in the field of science education where controlled conditions and fair tests are extensively emphasized in the introduction of scientific methods to students. We argue that it is the very same reason and in the interests of scientific rigor that educational psychologists study learning by isolating factors and controlling conditions for comparisons.
Relatedly, some objections have been raised to studies that compare and prefer explicit instruction over inquiry-based science teaching by suggesting that these studies equate inquiry-based science teaching to pure discovery without acknowledging that in reality, an extensive amount of guidance including explicit instruction is provided to students. We emphasize that these studies do not create exemplar curricula interventions to include teachers’ professional development, technologies, or argumentations that may sometimes include modules on explicit instruction, but only compare whether students learn better through practicing investigations or by being directly presented with the content. These studies simply suggest that having students practice investigations result in less understanding than having students directly interact with the content. We argue that such findings, mainly from controlled studies, at least warrant consideration in the formulation of educational policy. It must also be emphasized that just because an experiment only alters one factor at a time, it does not mean that the experimenter feels no other factor is important.
There is no more justification for excluding work based on randomized, controlled studies than there is for excluding work on exemplar curricula using program-based studies. As such, we must reiterate that our concern is not about the inclusion or use of program-based studies in policy documents, but solely on the complete exclusion of controlled studies from these documents.
Other objections are also raised to studies that alter one variable at a time on the grounds that classroom learning is complex with multiple variables interacting. This objection reflects a misunderstanding of the role of factorial experimental designs in determining the effects of interactions between factors. These studies do not violate the alter only one variable at a time rule. For example, the worked example effect occurs when learners presented worked examples to study learn more than those who learn by solving the equivalent problems (Chen et al., 2015, 2016). Nevertheless, based on the expertise reversal effect (Kalyuga et al., 2003), as levels of expertise in an area increase, the effect will decrease in size, then disappear, and eventually reverse with problem solving superior to studying worked examples. The effect can be demonstrated using a 2 (worked examples vs. problem solving) × 2 (lower expertise vs. higher expertise) experimental design with any statistically significant interaction effects explained by cognitive load theory (Paas et al., 2003).
Interactions between factors are important but they should not be solely handled by arbitrarily including a large number of random factors in an experiment. There are proper techniques for handling interactions and when used, the existence of interactions between factors does not violate the alter “one variable at a time rule.” Statistical interactions were specifically designed to deal with complexity. There is no excuse for the blanket exclusion of all such studies.
Acknowledging the essential role of direct, explicit instruction in hands-on activities that promote investigations, research has examined the sequential ordering of investigation-based explorations and direct explicit instruction. A number of studies suggest an integration model where explorations begin the sequence followed by direct explicit instruction (DeCaro & Rittle-Johnson, 2012; Jacobson et al., 2017; Kapur, 2008, 2010; Kapur & Bielaczyc, 2012; Loibl & Rummel, 2014; Schwartz & Martin, 2004; Weaver et al., 2018). It has been argued that the exploration process motivates students and activates their pre-existing knowledge. When receiving subsequent instruction, students’ prior problem-solving attempts enable them to better attend to critical concepts and allow them to see the subsequent instruction in a more meaningful and connected way (Kapur, 2008, 2010; Kapur & Bielaczyc, 2012). Interestingly, a recent meta-analysis by Loibl et al. (2017) reviewed various studies examining the approach of exploration followed by direct explicit instruction and found that this combination only works if the subsequent instruction specifically and directly explains the solutions to learners, which is parallel to what has been suggested in the direct, explicit instruction approach. In contrast, a number of studies support the relative effectiveness of direct explicit instruction first approach (Ashman et al., 2020; Fyfe et al., 2014; Glogger-Frey et al., 2015; Hsu et al., 2015; Matlen & Klahr, 2013; van Gog et al., 2011), arguing that starting with explorations overloads students’ working memory (Kirschner et al., 2006; Sweller, 2009; Sweller et al., 2007).
Pending more research, Ashman et al., (2020) proposed a theoretical perspective to explain this inconsistency using the concept of task complexity. The complexity of a given task depends on learners’ expertise. They argued that results favoring the exploration-first approach occur if learners are engaged in low complexity tasks. In contrast, when learners are involved in high complexity tasks, a direct explicit instruction first approach should be relatively effective.
Although there have been disagreements on the sequential orderings, none of these studies suggests that direct, explicit instruction is dispensable. Instead, these studies suggest direct explicit instruction is critical to science teaching and learning, a fact which does not seem to be acknowledged by standards over many years. In the absence of discussions addressing this issue in educational standards and reports, however, it is not uncommon to find teachers deliberately avoiding direct, explicit instruction in their attempts to implement instruction using investigations. For example, in observing lessons that adopt investigations, Furtak (2006) found that teachers often withhold concepts and procedures from students as a way to prioritize investigations. Abrahams and Millar (2008) also found that introducing students to concepts was often omitted in teaching that promoted investigations because teachers believe that the concepts and ideas will emerge from the act of investigation itself.
In summary, in the two previous sections, we presented contradictory results about teaching science through investigations by contrasting program-based studies with controlled studies. In the next section, we present a third methodology that has been used to address teaching through investigations.
Correlational Studies
Recently, correlational studies also have joined the conversation and started to examine procedures that emphasized teaching science through investigations. Most of these studies draw from large international data sets and use statistical techniques to look for correlations between specific instructional elements and students’ learning outcomes. Therefore, correlational studies differ from program-based studies that focus on testing the effectiveness of researcher-built inquiry-based programs as a whole. Moreover, those data sets tend to be a lot larger than those used by program-based studies. For example, TIMSS and PISA are two large initiatives collecting international data on students’ performance and self-reported learning experiences, such as how often they design and conduct scientific investigations in schools. Thus, the findings from correlational studies can provide information about whether the dissemination of the policy-suggested investigation approach to science teaching is effective over large populations. Furthermore, using statistical models, correlational studies can disentangle students’ learning experiences from one another. Coupled with multivariate designs to account for shared variance, correlational studies have unique access to associations between target learning experiences and students’ performance within a large population. While correlational studies cannot function in the same manner as randomized, controlled trials, they have an advantage in that they can more easily use very large data sets and make relationships evident. Thus, this form of research can help identify factors and patterns. For these reasons, correlational studies are more objective than program-based studies.
In contrast to widespread positive findings from program-based studies, correlational studies using large data sets have found that the more students were involved in inquiry-based investigation activities, the more their science learning outcomes dropped. This pattern has emerged over years and across countries and regions at different levels of science performance, in the USA (Kaya & Rice, 2010; Zhang & Li, 2019), Finland (Lavonen & Laaksonen, 2009), Qatar (Areepattamannil, 2012), Australia, Canada, New Zealand (McConney et al., 2014), Chinese inner-Mongolia (Gao et al., 2017), England (Jerrim et al., 2019), Norway (Teig et al., 2018), Ireland, the UK, and the other 4 countries listed above (Oliver et al., 2019), 54 countries (Cairns & Areepattamannil, 2019), 10 best and 10 worst performing countries (Aditomo & Klieme, 2020), and 13 countries at similar science achievement levels (Forbes et al., 2020), and Taiwan (Liou, 2020). Importantly, student-led, inquiry-based investigation that has been mostly suggested by world-wide science teaching standards has been identified as the least effective instructional element. For example, using PISA 2015 results (OECD, 2016) on instructional factors associated with science performance, it was found that having students involved in various investigation steps, such as arguing about science questions and conducting investigations, had negative associations. Forbes et al. (2020) noted that “highly student-driven dimensions of inquiry, particularly procedural activities associated with investigation, are least frequently associated with high levels of student science achievement” (p. 19). Martin et al. (2020) tested the effects of cognitive load reduction instructional procedures on student engagement and achievement. Load reduction instruction includes explicit instruction for novice learners in an area. The authors surveyed over 2000 secondary school science students concerning the extent to which load reduction instruction was used in their science classes and found a positive relation between load reduction instruction and engagement along with a positive relation between engagement and achievement. All these studies found that students’ high achievement is associated with teacher-directed, explicit instructional strategies.
This clear pattern has been interpreted in different ways. Some have suggested implications for educational practice by arguing that the negative association is clear evidence that the field has not done enough to support inquiry teaching in schools and should place more resources for and emphasis on inquiry, while others have raised calls for re-evaluating inquiry as an instructional approach. For example, finding the negative correlations between inquiry activities and students’ learning, Lavonen and Laaksonen (2009) insisted, “We do not suggest that the number of science inquiry activities should be reduced in Finland or in other OECD countries” (p. 937). Similarly, Aditomo and Klieme (2020) argued that “it would be misguided to use PISA findings to support arguments to scale back inquiry.” In contrast, Zhang and Li (2019) argued that “there might be some grounds for questioning the current way of characterizing scientific investigations and call on researchers to further examine this topic” (p. 342).
It is important to note that such studies often use survey data to collect students’ self-reported perceptions of what learning experiences they encounter, which are different from interventions that are strictly designed and consistently implemented across groups to test causal effects. As a result, correlational studies are limited in their capacity to claim causal relationships, which is also reflected in researchers’ various interpretations. They can, however, suggest factors of interest which then can and need to be tested in subsequent controlled studies.
Theoretical Issues Based on Cognitive Load Theory
In contrast to inquiry-based approaches, the explicit, structured approaches to instruction have strong, cognitively based theories underpinning them that are effective for generating predictions about learning gains and then explaining how and why these gains occurred. Cognitive load theory (Sweller et al., 2011, 2019) is one such theory and those aspects of the theory relevant to the current discussion will be briefly summarized. For categories of information relevant to instructional issues, the theory makes the following assumptions.
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Humans have evolved to automatically obtain novel information either by problem solving or from other people. It is far more efficient to obtain information from others than to generate it oneself during problem-solving.
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Once novel information is obtained, it must be processed by a limited capacity, limited duration working memory before being transferred to an unlimited long-term memory for later use. Compared to obtaining information from others, problem solving imposes a particularly heavy working memory load. Accordingly, we automatically gravitate to obtaining information from others. We engage in problem solving when we do not have others from whom we can obtain novel information.
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Once information is stored in long-term memory, it can be transferred back to working memory to govern action appropriate to a particular environment. Unlike when dealing with novel information, working memory has no known limits when dealing with familiar information transferred from long-term memory, resulting in the well-known transformative effects of education.
Based on cognitive load theory, there never is a justification for engaging in inquiry-based learning or any other pedagogically identical approaches when students need to acquire complex, novel information. As a species, we have evolved to obtain information from others and are particularly good at doing so. Data, especially from the worked example effect discussed above, provide strong empirical support, as do the correlation studies reviewed.
Summary of the Three Research Paradigms
In brief, we have summarized three contrasting ways researchers have used to deal with the same issue—teaching science through inquiry—or exploration-based investigations. The three categories demonstrate that different forms of educational research appear to generate very different findings and conclusions that vary from supporting inquiry as an overarching approach in field-initiated, program-based studies, to consistent negative associations in correlation studies, and to overwhelming results questioning inquiry in controlled studies. These disparate findings are, however, not reflected proportionally in current standards and reports. It is obvious that selecting a different category of research will result in different implications for educational practice. When writers of educational standards choose to follow only one methodology and ignore the others, this choice could be at the expense of students’ learning.
We argue that the success of future science education—and future scientists—relies on comprehensive standards that not only refer to a broader set of learning outcomes, but also represent a more balanced view of the available data. Thus, we further emphasize that none of the above should be seen as rejecting the use of any of the three research procedures discussed. But none of them alone should be used to definitively recommend any particular instructional procedure. Specifically, we should never use program-based studies as the sole source of evidence for any particular instructional procedure such as inquiry-based learning. All such recommendations should also include randomized controlled trials and large-scale correlational studies. However, program-based studies have been relied on almost exclusively in the standards to recommend inquiry-based learning with almost no questions addressed about the less favorable results from correlational and controlled studies. It is troubling to see sweeping curriculum reforms reinforced and overarching claims accepted while a large number of critical data sets have been ignored.
Barriers and Reflection on Practice
To close this article, we would like to summarize some difficulties we have seen and hope our discussion can offer those who share our concerns an opportunity to reflect on current practices and to bridge the evidence gap between various forms of research, especially research conducted within an educational psychology framework.
Randomized, controlled studies are a reliable source when generating implications for educational practice (Campbell & Stanley, 1966; Hedges & Schauer, 2018; Levin & O'Donnell, 1999; Mayer, 2003; Shavelson & Towne, 2002; Slavin, 2002; Whitehurst, 2002, 2003) and are commonly used by educational psychologists. In a recent review, Hedges and Schauer (2018) noted that there has been a dramatic decline in the use of randomized, controlled trials in education in the USA between 1980 and 2000. Specifically, in the field of science education, Taylor et al. (2016) found that a vast majority of impact studies were not conducive to quantitative synthesis. A review of research about inquiry-based science instruction by Minner et al. (2010) found that about 78% of the included studies either did not have a comparison group or used non-equivalent control groups. Our review is consistent with these reviews, finding evidence that controlled studies are underrepresented in educational standards and reports.
We understand that to many educators, designing interventions that alter one factor only is not a fair representation of the inquiry approach. Instead, they advocate the use of program-based studies that design exemplar programs including all relevant factors. We reiterate the key differences between these two types of study as discussed above and argue that it is the very reason why controlled studies are essential and desperately needed in the field. In advocating for randomized, controlled studies, we emphasize that the use of such studies does not preclude the use of other research procedures but similarly; the use of those other research procedures should not preclude the use of randomized controlled trials and correlational studies when determining appropriate instructional designs.
Because the nature of randomized, controlled studies is to control for factors, some educators have concerns that this type of study is lab-based and cannot take the classroom context into account. In fact, it is entirely possible to conduct these studies in real classroom settings, as shown in many published studies discussed above, and that to provide the most reliable suggestions for educational practice, controlled studies need to be replicated across contexts by different research teams.
Conclusions
Bridging the gap between research findings and educational practice can be difficult (Robinson et al., 2013; Wecker, 2013). We indicated that a large number of critical data sets have been neglected when formulating science educational policy, which has led to a disconnection between research findings and educational practice. We emphasize that none of the three research categories discussed should be rejected or used exclusively when determining instructional procedures. All can contribute useful information. Unfortunately, program-based studies seem to be almost the only category used. While important, these studies should never provide the sole data sets when determining instructional procedures. There are dangers that this approach has led and will continue to lead to less than ideal educational results.
Although we have focused our discussion on students’ understanding of science content and procedures, we acknowledge the importance of developing students’ other learning outcomes, such as interests in and attitudes toward science. We reiterate that we have no objections to the various science learning outcomes. Nor do we reject any data indicating that investigation activities can be included to achieve these different learning goals. We wish to argue, however, that effectively developing students’ understanding of science concepts and procedures should not be traded off by prioritizing other learning outcomes. It is hard to conceive of valid interests in and attitudes toward science without having the necessary conceptual knowledge and understanding.
There are many factors that are important to the success of science teaching. Elements, such as local contexts and resources, involvement of practitioners in collaborations, as well as nuances in the designed interventions, play important roles in the success of intervention implementations (Renkl, 2013, 2015; Wecker, 2013). However, we argue two points. First, randomly controlled trials have long been considered the only scientifically reliable procedure to establish a causal relationship. Second, we need to test whether such relationships can be effectively achieved in various contexts and what contextual elements and local practices affect the implementation. We believe the first point cannot be replaced by the second, or vice versa.
Change history
05 January 2024
A Correction to this paper has been published: https://doi.org/10.1007/s10648-024-09844-7
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Zhang, L., Kirschner, P.A., Cobern, W.W. et al. There is an Evidence Crisis in Science Educational Policy. Educ Psychol Rev 34, 1157–1176 (2022). https://doi.org/10.1007/s10648-021-09646-1
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DOI: https://doi.org/10.1007/s10648-021-09646-1