The advisability of science fair project topic origins: a case study of learners from disadvantaged backgrounds

doi:10.21203/rs.3.rs-4952188/v1

Download PDF

Research Article

The advisability of science fair project topic origins: a case study of learners from disadvantaged backgrounds

https://doi.org/10.21203/rs.3.rs-4952188/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

For learners from disadvantaged backgrounds with limited science fair-related skills, knowledge, and community support, investigating the advisability of various ways of arriving at a science fair project topic is needed. This mixed-methods case study uses questionnaire data and science fair awards regarding the engagement of 23 grade 9-10 learners in a year-long university-led intervention. Data analysis was conducted for four post-hoc determined topic-origin groups of these learners’ projects: internet, self, adult, and adult after the learner had displayed competence. Descriptive statistics and thematic analysis were used to determine whether each topic-origin group met the advisability criteria regarding learners’ perceptions of value and facilitators’ perceptions of feasibility. Each learner who was provided with a topic by an adult without first having displayed competence through designing a project of their choosing required unfeasibly high levels of facilitator input to remain in the programme. Generally, the greatest success was observed for the learners to whom an adult gave a topic after displaying competence. These findings and how the intervention was conducted are explained in terms of the four paradigms of learning and instructional design. A framework (Instruct-Expose-Explore-Formalise) for deriving science fair topics is suggested to enhance the efficiency and effectiveness of similar interventions.

Expo for Young Scientists Competition

extracurricular science enrichment

inquiry

education in poverty

teacher guidance

Inquiry refers to answering questions through analysing empirical data (Savery, 2019). In open inquiry, the learner is in control of all stages of the inquiry process, from choosing a topic to writing research questions, conceptualising and implementing data collection and analysis methods, to drawing conclusions and disseminating findings (Wang et al., 2022). Engagement in open inquiry can improve understanding of science and its nature (Zion et al., 2020), develop higher order thinking skills (Kind & Osborne, 2017), interest and motivation (Miller et al., 2018), and conceptual understanding (Sarioglan & Can, 2021). Science fairs, such as the South African (SA) Eskom Expo for Young Scientists (EYS) competition, allow learners to engage in open inquiry. However, learners from socioeconomically disadvantaged backgrounds, such as those attending SA low quintile schools (those serving poor communities), tend to have very low levels of science subject matter knowledge (SMK) (Reddy et al., 2016) as well as limited skills, including poor reading (Stott & Beelders, 2019), and verbal and written communication skills (Van der Berg et al., 2016). As novices, they experience high levels of cognitive load when engaging in inquiry (Emden, 2021). Even learners from more privileged contexts may find open inquiry prohibitively cognitively taxing (Kapici et al., 2022) and must first develop competence in more structured inquiry (Ramnarain & Hobden, 2015). Teachers at low-quintile SA schools are known to avoid inquiry (Ramnarain & Hlatswayo, 2018). It is, therefore, unsurprising that such learners tend to find engagement in science fairs such as the EYS overwhelming (Taylor, 2011). Naidoo (2021) found that such learners needed help identifying a science fair topic. Although there is a general understanding that learners should present open inquiry projects at science fairs, it is known that this often does not happen, particularly for learners from socioeconomically more advantaged backgrounds who have friends or family members who are highly qualified professionals who provide them with topics and other help (Bowen & Stelmach, 2020; Dabney et al., 2016). Learners from socioeconomically disadvantaged backgrounds, in contrast, are unlikely to have such human resources at their disposal (Mupezeni & Kriek, 2018) unless they are involved in an intervention (Ngcoza et al., 2016) where the facilitator may be able to provide them with a topic. However, the advisability of either a facilitator, friend, or family member doing so is yet to be known.

For a topic source to be considered advisable, this article assumes that two minimum criteria should be met: (1) the learners should report positive experiences regarding perceptions of learning value and that their basic psychological needs (BPN) were satisfied since, according to Self-Determination Theory (SDT), this improves learners’ general well-being, which also improves their learning (Ryan & Deci, 2000); (2) the facilitators should report that the learners were not so dependent on them for help that their output could be considered inappropriately distorted and/or logistically unfeasible. Once these criteria have been met, the quality of the learners’ outputs can further differentiate advisability.

Research questions

Learners can arrive at a science fair project topic from (1) direct or modified use of a topic from a resource such as a book or the internet, (2) their idea, (3) an adult’s suggestion after a learner has displayed some competence through first exploring their own topic which the adult then modifies, (4) an adult’s idea, perhaps somewhat inspired by the learner’s interests. Referring to these four topic origins, this research is guided by the general question: How do various science fair topic origins compare in advisability for high school learners from disadvantaged backgrounds? To answer this question, the following subquestions are responded to about a year-long science fair intervention started by 32 and completed by 23 grade 9–10 South African learners from disadvantaged backgrounds, who were retrospectively classified into these four topic origin groups:

What help did the learners receive from sources internal and external to the intervention?

To what extent did the learners in each topic origin group perceive that the intervention had learning value and that their basic psychological needs were satisfied during the intervention?

How did the topic origin groups differ in project quality?

How did the topic origin groups differ in the facilitators’ perceptions of the output quality per input cost?

Theoretical referents

The four paradigms of learning and instructional design (Cronjé, 2007) are used to describe the intervention’s intent, to interpret the facilitators’ perceptions of output quality per input cost in answer to the fourth research question, and to make suggestions in answer to the main research question regarding the advisability of various science fair topic origins. The Basic Psychological Needs (BPN) framework, a subdivision of Self-Determination Theory (SDT) (Ryan & Deci, 2000), guided instrument creation and data interpretation for the second research question. These theoretical referents are discussed below.

The four paradigms of learning and instructional design

A learning event may be plotted within Fig. 1 according to the extent to which it aligns with objectivism, related to the extent of teacher-led direct instruction involved, on the x-axis, and constructivism, related to the extent to which learners can engage in sense-making activities, on the y-axis (Aylward & Cronjé, 2022).

Insert Fig. 1 here

The plane’s quadrants describe instructional styles which target specific learning outcomes and are appropriate for particular levels of learner mastery. These are injection (e.g., direct instruction), immersion (e.g., incidental, experiential learning), construction (e.g., problem-based learning), and integration (in which direct instruction or attention to external, objective principles is alternated with engagement in active sense-making by the learners). Aylward and Cronjé (2022) assert that a clockwise progression from injection through to integration is generally appropriate as learners progress from the novice state (unconsciously incompetent, followed by consciously incompetent), where direct instruction (injection) is needed to supplant incorrect knowledge and develop knowledge and skills through tuition, demonstration, and reproduction; through to intermediate levels of conscious competence, where they are required to engage in the application of knowledge to complex contexts (construction); ending in expert states in which the learners can be expected to autonomously and seamlessly integrate objectivist and constructive elements (integration). Although this may be the general progression of instruction, the reality is more complex than this, requiring oscillations between the quadrants, as well as entry into the immersion quadrant, sometimes intentionally (e.g., through service-learning opportunities) or incidentally, perhaps as a learner grapples unaided, and largely unproductively, with a problem.

A science fair project ideally requires a learner to operate in the integration quadrant. Producing an experimental investigation for a science fair project involves learning which is high on the constructivist axis of Fig. 1, since the learner must autonomously apply a scientific epistemology to build knowledge through a complex sense-making process. However, this must be done systematically within the confines of the so-called Scientific Method to meet the judging requirements of science fairs such as the South African Expo for Young Scientists competition. This is one sense in which this activity lies on the further right end of the objectivist. Furthermore, since science fair participants are child learners, they are expected to be novices in the fields in which they situate their projects and, therefore, experience a high cognitive load (Emden, 2021), requiring reduction by adult input. Some of this input may be viewed as generative scaffolding, which enhances the constructivist dimension of the activity by empowering sense-making activity (Aylward & Cronjé, 2022). Some may instead be viewed as supplantive, stipulative direct instruction, which enhances the objectivist dimension (Aylward & Cronjé, 2022). One aspect of this input may be external guidance regarding the project topic, which may also be seen as contributing to the learning's constructivist and/or objectivist dimensions, depending on the extent of internalisation by the learner.

Basic Psychological Need Satisfaction (BPNS)

In education, BPN posits that learning happens best when learners’ needs for autonomy, competence, and relatedness are met (Ryan & Deci, 2000). In the context of an intervention, these constructs refer to learners’ perceptions that the intervention aligns with their values (autonomy), their knowledge and skill levels improve and are recognised (competence), and the extent and quality of their interpersonal relationships develop through the intervention (relatedness) (Ryan & Deci, 2000).

This is a pragmatically conducted mixed methods exploratory case study guided by the Framework for Integrated Methodologies (FraIM) (Plowright, 2011). Both quantitative and qualitative data were collected simultaneously. The quantitative data were focused on during analysis, followed by a search for confirming and disconfirming evidence within the qualitative data. Warrantability is a proxy for validity within FraIM (Plowright, 2011). This requires sufficient reporting transparency to allow readers to judge the extent to which claims are warranted within reported contextual constraints. In addition to attempting to provide this transparency, the second facilitator served as a critical reader. She confirmed that the descriptions, findings, and conclusions aligned with her experiences in the intervention.

Sample

Data were collected from each of the 23 learners who completed the intervention. These were part of 32 learners selected from 100 grade 9s engaged in an extracurricular intervention preceding the one reported here. Their teachers had identified these 100 as being higher achievers in mathematics and natural sciences, with approximately 20 being drawn from each of five quintile 1–3 schools near the SA university campus where the interventions were held. These 100 were exposed to three 2-hour sessions about planning an EYS experimental investigation, after which 86 submitted their plans. Of those who wanted to participate, the 32 who produced the best plans were chosen for inclusion in the intervention to which this research is related. All 32 learners and their guardians provided informed written consent for inclusion in this research. However, the reported data was collected from only the 23 who completed the intervention and the two facilitators who conducted it.

Intervention

The year-long intervention was spread over 30 sessions, with 140 hours of contact time. All the sessions were conducted in a computer laboratory on a university campus, with each learner working at an internet-connected computer. The first six months of the intervention were intended for topic origination, involved 59 hours of contact time over 12 sessions, and were conducted by only one facilitator, the researcher. The term topic origination is taken to include explaining the main terms and concepts of the chosen topic, identifying independent and dependent variables, formulating a focus question, identifying variables to be controlled, treatments to be set up, and equipment needed, and describing the data collection process.

During these topic origination sessions, the learners worked through the first nine steps (Introduction, Topic, Literature, Referencing, Background knowledge and brainstorming, Evaluation, Variables and focus questions, Fair testing, Method and hypothesis) within the online programme Your Science Fair Investigation, available at https://www.learnscience.co.za/challenge-page/your-first-science-fair-investigation. This programme first exposes learners to previous learners’ project ideas through photographs, written stories, and videos, directs learners to explore the Science Buddies website, and requires them to list and brainstorm their interests. After this, they are taught and practice how to access, summarise and reference literature. They are guided to identify variables and their indicators, pose focus questions and hypotheses, design fair tests, and are introduced to quantitative and qualitative measurements, instruments, and their units.

The intervention also included a structured, intelligent Excel sheet called the Investigation guide that the learners incrementally completed, guided by the face-to-face teaching sessions, the online programme, and individual discussions with the facilitator. The learners were also occasionally required to explain their evolving ideas to one another in small groups and were frequently encouraged to help one another informally. Each learner’s Investigation guide, hosted on OneDrive, was always accessible to both the learner and facilitator. The facilitator could also view the learners’ responses within the online programme through its back end. Throughout this period, the facilitator accessed each learner’s work and provided individualised written feedback via email between successive sessions. Few of the learners had even basic computer literacy skills at the start of the intervention, so a session early in the intervention period was dedicated to setting up email accounts and teaching the learners computer usage basics. Even after this, considerable time was spent in each session, particularly at the start of the intervention, helping the learners develop computer literacy skills.

Each session began with an approximately hour-long direct instruction session in which the facilitator taught a face-to-face version of the corresponding part of the online programme. This was followed by two to six-hour periods of individual work. The length of each session depended on transport arrangements since no transport budget could be obtained, necessitating dependence on rather erratic help from various sources. During the individual work period, the learners were given a list of tasks to perform. These always included engaging with the written feedback from the facilitator, completing the relevant activities in the online programme and the relevant sections of the intelligent Investigation guide, and asking for help from the facilitator as required. After helping those who asked for help, the facilitator individually checked on as many others as time allowed.

Much of what was done in these first six months of the intervention, particularly during the first two hours of each session, was injection pedagogy (Aylward & Cronjé, 2022) since the aim was to teach the learners how to conduct an experimental investigation through direct face-to-face instruction, supplemented by activities in the online programme. It soon became clear that the learners’ knowledge of science, understanding of how to conduct an experimental investigation validly, and reading skills were limited, as is established in the literature, even for higher achieving learners from low-quintile South African schools (Stott & Beelders, 2019; Stott & Duvenhage, 2023). Therefore, beginning the intervention with a primarily teacher-centred injection pedagogy was appropriate (Aylward & Cronjé, 2022). The intelligent electronic Investigation guide was a scaffolding tool to support the learners to apply what they learned through injection to their project, moving them along the vertical, constructivist axis in Fig. 1.

Figure 2 represents the number of learners over the duration of the intervention, according to the origin of their project topic. This was informed by records, per learner, of attendance, facilitator guidance, and topic for each of the 30 sessions across the intervention, coupled with field notes written shortly after each session. As indicated on the left-hand side of this diagram, 24 of the 32 learners decided, early in the intervention, either on a topic they got from the internet (9) or their own idea (15). For six of the learners who formulated their own ideas, this was relatively drastically modified by the facilitator a few months into the process, to the extent that their topic could better be described as coming from an adult after the learner had displayed some competence. It should be noted that the facilitator continually gave all the learners individualised feedback and that all topics evolved.

Insert Fig. 2 here

As indicated in Fig. 2, an additional facilitator joined the intervention at the end of the first six months and provided a topic to the nine learners who still needed to formulate a viable topic. The 23 learners who completed their projects fell into the topic-origin categories: internet (5), self (7), adult after the learner has displayed competence, referred to hereafter as adult-after-competence (4), and adult (7). The facilitators each had over ten years of experience teaching the sciences at the high school level. During that time, they mentored learners to produce high-quality projects, some of which won medals at regional, national, and international science fairs.

These groups are not experimentally comparable since they differ in many ways, invalidating any positivist comparison. However, the data collected about members of each group are considered valuable in contributing to an understanding of the advisability of adopting each of the manners of arriving at a research topic for a science fair project when interpreted within the constraints of how these groups arose, as explained below and elsewhere in this article.

The facilitators sufficiently modified some learners' topics for them to be classified in the adult-after-competence group. Reasons for this include the learners’ receptivity to the facilitator's input, self-direction and introversion, the scope their self-originated topic offered for improvement, and local conditions. Four examples are given to illustrate this. Learner A started out showing an interest in the heat conductivity of various materials. The facilitator suggested asking elders in his community for indigenous forms of thermal insulation, such as local materials used in insulating hot pot mats. Over the next six months, he was absent for some sessions, failed to submit work for checking, rarely asked for help and only responded superficially to e-mail and verbal prompts from the facilitator. At that point, all learners without viable topics were given three options: to propose one by the following week, to receive a new topic from the new facilitator, or to drop out of the programme. Learner A chose the first of these, which involved testing the time it took water to boil in each of two pots of different materials. He, therefore, fell into the self-originated topic origin group. Learners B and C both serve as examples of the adult-after-competence group. Learner B completed an internet-inspired project within the programme's first six months. A few weeks after the second facilitator came, one of the learners to whom she gave an idea dropped out of the programme. Learner B took on that idea under the second facilitator's guidance and submitted that project, rather than his first one, at the science fair. Early in the intervention, Learner C showed interest in soil types. Guided by the individual written feedback that the facilitator gave to all the learners, her topic submissions evolved over the first few months from testing how well plants grow in various types of soil to measuring soil pH and soil clay content to the influence of soil clay content on water expansion. Under the facilitator's general guidance, Learner C provided a complete plan for performing an investigation for the last of these, therefore displaying competence in investigation design. At this point, the facilitator consulted an expert in soil mechanics, who provided Learner C with a modified topic: the rate of water expansion of montmorillonite relative to that of clay known to cause structural damage and the testing of a simple device to determine water expansion rate. This expert provided the necessary equipment and specialist guidance from that point onward. Learner D, an introverted and self-directed learner, chose a viable project from the internet early in the intervention and rarely asked for help. Since she was observed to work diligently and competently, the facilitators tended to forget about her as they focused on learners who more clearly appeared to need their help. The facilitator, therefore, did not suggest a change to Learner D’s internet-generated topic despite her display of competence.

Data collection

To answer the first research question regarding the help the learners received, the 23 learners who completed the intervention answered a 28-item closed-response and one-item open-response questionnaire at the intervention’s conclusion. The purpose of this research question was to evaluate the validity of the assumption that the learners received negligible help in deriving their topic beyond what was provided in the intervention and, therefore, known to the researcher.

To answer the second research question, regarding the learners’ perceptions of learning value and the extent to which their BPNs were satisfied, questionnaire data were collected at the end of the intervention from the 23 learners who completed it. This research question aimed to determine whether the first criterion of advisability listed in the Introduction was met for each group. The questionnaire data was of two main types. For both types, the Likert scale items used had five items with the descriptors: 1: strongly disagree, 2: disagree, 3: neutral, 4: agree, 5: strongly agree. The first of these two types comprised 58 Likert, and 4 open items regarding the learners’ perception of the learning they underwent, the enjoyment they experienced, and their perception of value, of various components of the intervention. The second was the basic psychological needs satisfaction index questionnaire (BPNS) obtained from Van der Kaap-Deeder et al. (2020) and modified slightly to refer to the intervention. This consisted of 28 Likert items measuring perceptions of competence (6), relatedness to peers (8), relatedness to adults (5), and autonomy (9).

An index of project quality was derived per learner to answer the third research question regarding the quality of the learners’ projects for the various ways of arriving at a project topic. To enhance validity, this index was derived from two equally weighted sources, as indicated in Table 1: (a) the quantified outcome of the EYS competition; (b) a facilitator quality rating derived from seven 5-item Likert scale questions, answered at the end of the intervention by the facilitator responsible for that learner. The answer to the third research question is foundational to answering the fourth research question.

Table 1

Derivation of the project quality rating (/12)
Information source	Item	Score
Outcomes of the EYS Competition	Medal at the regional competition	Bronze: 1 Silver: 2 Gold: 3
	Shortlisting for national competition Special prize at regional or national competition /	1 additional point for each item
		6 points maximum
Facilitator rating	Topic quality	5-point Likert scale for each of these, giving a maximum of 35 points possible
	Method rigour, depth, quality
	Quality of data representation
	Quality of data analysis, limitations, significance and conclusions
	Quality of report
	Quality of poster
	Quality of verbal discussion
		Scaled to 6 points maximum
TOTAL		12 points maximum

Insert Table 1 here

The fourth research question is related to the output quality compared to the input cost for each topic origin group. The quality index derived to answer the third research question was used as a proxy for output quality. To obtain an index to represent input cost, at the end of the intervention, each facilitator answered 5-point Likert questions for each learner they had facilitated regarding the amount of help they had provided throughout the intervention for each of six aspects of the project (choosing a topic, planning the method, collecting the data, representing and analysing the data, writing the report and poster and editing the report and poster). This research question aimed to determine whether the projects in the various topic source groups met the second criterion for advisability listed in the Introduction and to differentiate further those that met both advisability criteria based on their quality.

Data analysis

A frequency graph of individual responses was used to represent the data regarding the learners’ sources of help, aiding pattern searching to answer the first research question. Quantitative and qualitative data were collected to answer the second research question regarding the learners’ perceptions of learning value and the extent to which their basic psychological needs were satisfied. The quantitative data were analysed by calculating the sum of the Likert scale scores per dimension for each topic origin category after having reverse-coded the reversed items from the BPNS questionnaire. The qualitative data were analysed through inductive identification of themes, followed by extraction of statements that appeared to confirm or disconfirm trends that emerged from the quantitative analysis. To decide whether acceptability criterion (1), regarding learners’ perceptions of learning value and BPN satisfaction, on average, by a topic origin group, an arbitrarily defined threshold of 50% per questionnaire category was used. The deductions made from this were evaluated for validity against the qualitative findings.

To facilitate pattern recognition to answer the third research question regarding project quality, five project quality categories, ranging from very poor to very good, were defined based on arbitrarily defined thresholds within the project quality index. These thresholds were chosen to distribute the projects evenly among the categories.

Categories were created to answer the fourth research question regarding input cost relative to output value. The indices used as proxies to these variables were plotted against one another, with each learner being represented by one point in this graph. Clusters of points were given quality per cost category labels using arbitrary thresholds, followed by a discussion between the facilitators about the validity of these labels and refinement of these thresholds to match the facilitators’ perceptions. After this input-output category formation, the number of learners per input-output category was plotted per topic origin group to aid the evaluation of the topic origin groups against advisability criterion (2) and the consideration of relative value.

The findings of each research question are presented below, headed by a claim that briefly answers the corresponding research question.

Learners were heavily dependent on the intervention for help throughout their projects.

Figure 3 represents the learners’ answers regarding the help they received. The length of each bar colour indicates the number of learners who reported receiving that kind of help from the indicated source. Since no limit was placed on the number of types of help each learner could indicate per source, the total length of some bars exceeds the number of learners (n = 23).

Insert Fig. 3 here

The bottom three bars refer to help sources outside of the intervention. The types of help can be divided into cognitive (shades of orange), emotional, and material (shades of grey). Figure 3 shows that the learners were heavily dependent on the intervention for cognitive help. The relatively little help they received external to the intervention was mostly emotional.

All groups perceived the process positively, with slight differences between the groups

Figure 4 shows the average score per learner perception dimension per topic origin group. The finding that all these scores were above 70% suggests that all four of the topic origin groups had generally high perceptions of learning value. The adult-after-competence group typically displayed the most positive perceptions. The qualitative data supported the finding of general positivity. Comments indicating high levels of engagement were abundant for all groups. Examples include, ‘When I collected data, I kept repeating the experiment for a month to get the best result’; ‘I learned how to read and summarise’; ‘It was challenging, and I like challenges’; ‘Here at science expo, we get to explore and increase our knowledge of things’ ; ‘I was able to complete a good project that I am also proud of, and I couldn`t have done it without this program’

Insert Fig. 4 here

Figure 5 represents the data gathered from the BPNS questionnaire. This reveals considerably higher scores for competence and autonomy (all above 78%) than relatedness (58–71%), particularly for peer-relatedness (58–67%), for all the topic origin groups. This corresponds to one of the learners’ statements that they tended to work alone on their computers, and perhaps there should have been more discussion. This isolation related to individual computer usage was pronounced for those learners who self-originated their project topics or derived them from the internet, as shown by both groups’ low levels of relatedness to peers (61 and 58%, respectively) and the internet group’s low relatedness to adults (62%). Learners from the internet group commented, ‘Lack of mentor feedback and evaluation and insufficient guidance’; ‘The monitors should check the participants’ work regularly and not take their responses, as many participants will be thinking they are doing the correct things whereas they aren`t.’ In contrast, some of the learners from other groups commented on high levels of interaction with peers and, particularly in groups where the adult contributed significantly to the topic origin, with the facilitators. For example, ‘The best thing in this Expo programme is making friends and learning to present my work without fear.’; ‘The teachers helped me make a good project by showing me my mistakes and how to fix them, and my expo classmates helped and taught me how to explain my project to others.’ The quantitative and qualitative data from the learners support what the facilitators reported, namely that some were so dependent on the facilitators that they neglected other more self-directed, quieter, and less demanding learners. This is clarified further in the section that answers the fourth research question below.

Insert Fig. 5 here

The relatively low average competence perceptions of the learners in the adult-after-competence group (Fig. 5) contradict the high score derived from external assessment for this group in Fig. 4. This discrepancy may be due to these learners tending to be more differentiated and self-critical in their evaluation, as suggested by this comment: ‘I said I didn't learn to the maximum because there were other things I already knew and because on other things, I didn't learn every feature of other parts like the excel, and also because some parts were not crucial to my project.’

Projects with more teacher topic input tended to be of higher quality

Figure 6 indicates the proportion of learners in each topic origin group according to the project quality category. All these projects won medals at the EYS competition, so the category names very low and low are inappropriate in absolute terms. They are used here relative to other projects in this intervention.

Insert Fig. 6 here

Although Fig. 6 indicates a range of project quality for each project topic origin type, it shows that greater adult involvement in topic origin was generally associated with better project quality. This is even though the nine learners given topics by an adult (halfway through the intervention) were likely weaker since they would otherwise have dropped out. The greatest project quality was obtained when an adult gave a topic after the learner had demonstrated some competence.

The facilitator perceived the groups differently regarding output per input

In Fig. 7 each project is plotted according to the facilitator’s perception of her overall input versus the project quality, i.e., output. As has been explained, the facilitators provided input throughout the intervention according to learner requests, their perceptions of learner needs, and time availability. As with Fig. 6, Fig. 7’s labels should be interpreted relatively. For example, as shown above, all the learners benefited greatly from this intervention and achieved medals for their projects, making the term fruitless toil inaccurate in absolute terms.

Insert Fig. 7 here

Figure 8 indicates the frequency of learners from each of the input-output category groups defined in Fig. 7 per topic origin group. Unlike the other findings, differences are very pronounced here, with those learners who received a topic from an adult being rated as requiring what could be considered so much input that their high achievements were not a true reflection of their ability (distorted input), or to have achieved relatively low outputs despite a large amount of input (fruitless toil). It should be remembered that these learners would have fallen out of the intervention if they had not been given a topic by an adult facilitator in the intervention. As seen in Fig. 7, a facilitator provided these learners much help throughout the intervention, not only regarding the topic. This was because of their high degree of dependence. Despite this, these learners exhibited high perceptions of autonomy and competence (Fig. 6). Most learners in the adult-after-competence group were classified as the effortful impact group, meaning they produced high-quality projects. Although the facilitators provided them with much help, the extent of this was not considered excessive. Most learners who found a topic themselves (internet and self groups) were classified as easy but limited because the facilitators did not provide them with much one-on-one help since they did not ask for much help. They did not appear to need this to remain in the intervention, and their projects were of relatively low quality. Some of the learners in these two groups did, however, produce high-quality projects: in the internet group despite receiving little individual help throughout the intervention and in the self group with considerable, but not excessive, help.

Insert Fig. 8 here

The finding that the learners were heavily dependent on the intervention for help throughout their project validates the assumption that this research was based on, that the input provided within the intervention, and therefore known to the researcher, was the only significant contributor to the learners’ project topic origins. This is consistent with what is known about generally low support levels that learners from low socio-economic backgrounds receive for science fair participation both at home and school in South Africa (Mupezeni & Kriek, 2018) and even in developed countries such as the United States of America (Delisi et al., 2020). This contrasts with learners from more privileged contexts tending to receive much assistance from friends and family, who may even be experts in the project’s topic (Bowen & Stelmach, 2020).

All groups were considered to meet advisability criterion (1) regarding perceptions of learning value and basic psychological need satisfaction since all achieved above 50% on average for each of the subdimensions measured. Regarding learning value and perceptions of competence and autonomy, all groups achieved above 75%. Regarding relatedness, however, the internet group’s low scores for peer and adult relatedness and qualitative evidence that this group felt neglected are of concern. This corresponds to the input information plotted in Fig. 8, which shows very high levels of facilitator input for some learners, for many of whom this resulted in a distorted impact, contrasted with relatively low levels of input throughout the intervention for learners in the internet- and self-topic origin groups. The deduction can likely be made that had the facilitators’ time been freed up by reducing help to the ‘distorted impact’ learners, the self and internet groups could have been given more help, likely improving their relatedness and project quality.

The high level of perceptions of autonomy of all the groups, including those to whom an adult gave a project (Fig. 5), is important since it negates the intuitive assumption that high adult involvement may disqualify advisability due to failing to meet the dimension of autonomy within the learning value and BPNS criterion. This can be understood relative to their general experience at school, as well as cultural perceptions of control. Besides the fact that all South African public schools follow a highly stipulated, content-heavy curriculum, which allows little scope for independent learner work (Bertram et al., 2021), this is more pronounced in low-quintile schools such as those attended by the learners in this program (Ramnarain & Hlatswayo, 2018). Additionally, African cultures tend to be communally oriented and value respect for authorities (Muller & Hoadley, 2019). People from cultures with such orientations and values may prefer a higher degree of guidance than people from more individualistically oriented cultures (Chirkov et al., 2003). Within Self-Determination Theory, autonomy refers to alignment with personal values (Chirkov et al., 2003), making it possible for a person to score highly for autonomy in cases where they view receiving much external direction as consistent with their interests and culture.

All the learners to whom an adult gave a topic to prevent them from falling out of the intervention required excessive amounts of facilitator help, with about half producing projects of distortedly high quality. This group, therefore, fails advisability criterion (2) regarding feasibility and avoidance of distortion. In contrast, those learners who were required to display competence by first planning a project from a self-originated idea, after which the adult significantly modified this, required levels of input that the facilitators considered reasonable, although high. This suggests that an adult should not give a learner a topic without them first having displayed competence. This deduction implies that the seven completing learners for whom this was the case should have dropped out of this intervention despite the benefits they gained from it. Besides the unreasonably high workload their heavily supported continuation placed on the facilitators, with decreased support for other learners, the distorted impact they attained is inappropriate.

Finally, the findings show that it is possible for learners, even from low-quintile South African schools, to produce high-quality projects from internet-derived or self-originated project ideas within a supportive intervention context as described. However, as discussed above, it appears more likely that such projects will be low quality. Also, dropout appears more likely when adults are less involved in topic origination.

We could explain these findings using the four paradigms of learning and instructional design (Aylward & Cronjé, 2022) as follows. After the learners had received direct instruction and practice within the injection zone, they were tasked with applying this knowledge to their project, with the choice of a topic being the first step in this process. Scaffolding, provided in multiple forms, was intended to support the integration of the learner’s own ideas (high on the constructivist axis) within the confines of the guidelines for a scientific investigation (high on the objectivist axis). However, learners need considerable competence to operate productively in this quadrant. So, although this was the pedagogical intention, the reality was rather that the learners may have found themselves in the immersion quadrant, which Aylward and Cronjé (2022) occasionally refer to as the chaos zone since it is low in structure and is often associated with little productive progress. Several (10) fell out of the intervention before emerging from this. Some were able to emerge by themselves, possibly with the help of the Internet and the facilitator. Others remained in this immersion quadrant despite the presence of resources and facilitation. These would have dropped out if the second facilitator had not provided them with a project. However, since they had yet to demonstrate the ability to make progress on the constructivist axis, they remained dependent to a large degree.

Unsurprisingly, a considerable number of the learners benefited from an adult giving them a topic: six (four of whom completed their projects) after they had displayed some competence, and eight to prevent them from falling out of the intervention due to failing to arrive at a feasible topic by other means (although one of these did subsequently fall out before completion). This is because even higher achieving learners from low-quintile South African schools, such as the learners in this study, are known to tend to have limited skill and knowledge levels (Stott & Beelders, 2019; Stott & Duvenhage, 2023) and, therefore, be particularly in need of external guidance (Naidoo, 2021), and, as shown in Fig. 3, to receive little cognitive help for their project external to the intervention.

Limitations and suggestions for further investigation

The study’s limitations include the small sample size (23) and the lack of comparability of the post-hoc determined groups. Care has been taken to be transparent about the process that resulted in these groups and not to overreach the claims made from the data considering this limitation. Although a large-scale quasi-experiment may provide more valid data on the advisability of various science fair topic origins, its logistical and ethical considerations are likely prohibitive. The nature of the intervention and the characteristics of the facilitators are also important and complex but non-replicable contributors to the reported outputs. Descriptions have been given as transparently as space has permitted to reduce these limitations. The long duration of the intervention and the learners’ heavy dependence on the facilitators due to their disadvantaged home contexts, as is partly shown in Fig. 3, made this a demanding and expensive intervention, limiting the likelihood of a comparable intervention. This limitation suggests an even greater need for adult input in the project topic after the learners have displayed appropriate competence to enhance efficiency in a shorter intervention. Finally, the conclusions of this study may be limited to learners from disadvantaged backgrounds. Learners with greater skill and knowledge levels due to the educational advantages linked to higher socioeconomic status may be more able to self-originate high-quality topics for science fair projects without the adult input this study found to be generally needed. Higher skill and knowledge levels decrease cognitive load, freeing up working memory space for creativity (Gong et al., 2023).

Suggestions for practice: The Instruct-Expose-Explore-Formalise Framework

The framework given in Table 2 is suggested as an instructional sequence to guide topic origination in science-fair interventions, at least for learners from disadvantaged backgrounds, but possibly more generally. As indicated in the final column, the four stages correspond to the four quadrants of the four paradigms of learning and instructional design (Aylward & Cronjé, 2022). This begins (Instruct) with a period of direct instruction in the Scientific Method. This aims at developing the learners’ understanding of variables, fair testing, questioning, hypothesising, and measuring. This is followed (Explore) by learners being exposed to stimuli that can help them brainstorm topics they may be interested in, such as attending a science fair. After this the learners are expected to apply what they learned during the Instruct stage to design an experiment of their own topic origin (Explore). For efficiency, it may be appropriate for the learner to get ideas from sources such as books and the internet if they cannot think of a topic themselves. This stage aims to deepen their understanding of what was taught in the Instruct phase and display competence in doing this. Therefore, the topic need not be original or valuable. Before progressing to the final stage, Formalise, learners who have been unable to display competence in a topic of their own choice should drop out of the intervention since their retention is likely to result in unfeasible demands on facilitators and distorted outputs. In the Formalise stage, a knowledgeable adult, such as the facilitator, suggests a topic, perhaps modified from the learner’s own. The learner then internalises and possibly modifies this as they design an experiment based on it, guided by the Scientific Method. Although this framework suggests a sequential progression through the stages, some back-and-forth movement between the stages may likely be preferable and necessary.

Table 2

The Instruct-Expose-Explore-Formalise framework for science fair topic origination
Stage of science fair topic origination	Description	Purpose	Quadrant in the four paradigms of learning and instructional design (Cronjé, 2007)
1: Instruct	Learners receive direct instruction in the Scientific Method	Develop knowledge about experimental design, for application in subsequent stages	Injection
2: Expose	Learners are exposed to a wide range of ideas, e.g., through seeing other learners’ science fair projects	Stimulate learners to brainstorm for a science fair idea that they would find interesting	Immersion
3: Explore	Learners are required to produce a comprehensive project plan about a topic of their own choosing	Provide learners with the opportunity to display competence in applying what they learned in stage 1 to a new context	Construction
4: Formalise	An adult suggests modifications to the learner’s own topic or possibly negotiates an entirely different topic with the learner, after which the learner produces a comprehensive project plan on this topic in a way that meets guidelines and criteria stipulated in the Scientific Method	Produce a high-quality project plan with an appropriate level of adult assistance	Integration

Insert Table 2 here

Author Contribution

This is a sole author manuscript. All aspects of the research and authorship were conducted by the author.

Data Availability

The data cannot be shared publically to protect the participants' privacy.

Disclosure statement

The author report there are no competing interests to declare.

Ethics statement

Ethical clearance was obtained from the University of the Free State’s Faculty of Education ethics committee (UFS-HSD2019/0011/22).

Aylward, R. C., & Cronjé, J. C. (2022). Paradigms extended: how to integrate behaviorism, constructivism, knowledge domain, and learner mastery in instructional design. Educational Technology Research and Development, 70(2), 503–529. https://doi.org/10.1007/s11423-022-10089-w
Bertram, C. A., Mthiyane, C. C. N., & Naidoo, J. (2021). The tension between curriculum coverage and quality learning: The experiences of South African teachers. International Journal of Educational Development, 81, 1–8. https://doi.org/10.1016/j.ijedudev.2021.102353
Bowen, G. M., & Stelmach, B. (2020). Parental Helping with Science Fair Projects : a Case Study. 342–354.
Chirkov, V., Ryan, R. M., Kim, Y., & Kaplan, U. (2003). Differentiating autonomy from individualism and independence: A self-determination theory perspective on internalization of cultural orientations and well-being. Journal of Personality and Social Psychology, 84(1), 97–110.
Cronjé, J. (2007). Towards integrating objectivism and constructivism in instructional design and learning sciences. Educational Technology Research and Development, 54(4), 387–416.
Dabney, K. P., Tai, R. H., & Scott, M. R. (2016). Informal Science: Family Education, Experiences, and Initial Interest in Science. International Journal of Science Education, Part B: Communication and Public Engagement, 6(3), 263–282. https://doi.org/10.1080/21548455.2015.1058990
Delisi, J., Kook, J. F., Fields, E., Winfield, L., & Levy, A. J. (2020). An examination of the features of science fairs that support students ’ understandings of science and engineering practices. September, 491–519. https://doi.org/10.1002/tea.21669
Emden, M. (2021). Reintroducing “the” Scientific Method to Introduce Scientific Inquiry in Schools? A Cautioning Plea Not to Throw Out the Baby with the Bathwater. Science & Education, 30(5), 1037–1073.
Gong, Z., Miao, K., Liu, X., Luo, M., Yu, Y., & Chen, Z. (2023). A Positive Association between Working Memory Capacity and Human Creativity: A Meta-Analytic Evidence. Journal of Intelligence, 11(1). https://doi.org/10.3390/jintelligence11010015
Kapici, H. O., Akcay, H., & Cakir, H. (2022). Investigating the effects of different levels of guidance in inquiry-based hands-on and virtual science laboratories. International Journal of Science Education, 44(2), 324–345. https://doi.org/10.1080/09500693.2022.2028926
Kind, P., & Osborne, J. (2017). Styles of Scientific Reasoning: A Cultural Rationale for Science Education? Science Education, 101(1), 8–31. https://doi.org/10.1002/sce.21251
Miller, K., Sonnert, G., & Sadler, P. (2018). The influence of students’ participation in STEM competitions on their interest in STEM careers. International Journal of Science Education, Part B: Communication and Public Engagement, 8(2), 95–114. https://doi.org/10.1080/21548455.2017.1397298
Muller, J., & Hoadley, U. (2019). Changing forms of curriculum and governance in developing countries. In N. Spaull & J. Jansen (Eds.), South African Schooling: The Enigma of Inequality. Policy Implications of Research in Education, vol 10 (pp. 109–125). Springer. https://doi.org/10.1007/978-3-030-18811-5_6
Mupezeni, S., & Kriek, J. (2018). Out-of-school activity: A comparison of the experiences of rural and urban participants in science fairs in the Limpopo Province, South Africa. EURASIA Journal of Mathematics, Science and Technology Education, 14(8), em1577.
Naidoo, K. (2021). Understanding Self-Regulated Learning and Self-Efficacy in Project-Based activities: Case Studies of selected Eskom Expo for Young Scientists Alumni. In John Butler-Adam (Ed.), STEMI Olympiads and Competitions Community of Practice Conference (pp. 65–87). South African Agency for Science and Technology Advancement.
Ngcoza, K. M., Sewry, J., Chikunda, C., & Kahenge, W. (2016). Stakeholders’ Perceptions of Participation in Science Expos: A South African Case Study. African Journal of Research in Mathematics, Science and Technology Education, 20(2), 189–199.
Plowright, D. (2011). Using mixed methods: Frameworks for an integrated methodology. SAGE Publications.
Ramnarain, U. D., & Hlatswayo, M. (2018). Teacher beliefs and attitudes about inquiry-based learning in a rural school district in South Africa. South African Journal of Education, 38(1), 51–61.
Ramnarain, U. D., & Hobden, P. (2015). Shifting South African learners towards greater autonomy in scientific investigations. Journal of Curriculum Studies, 47(1), 94–121. https://doi.org/https://doi.org/10.1080/00220272.2014.966153
Reddy, V., Visser, M., Winnaar, L., Arends, F., Juan, A. L., Prinsloo, C., Isdale, K., & Reddy, V., Visser, M., Winnaar, L., Arends, F., Juan, A.L., Prinsloo, C. & Isdale, K. (2016). TIMSS 2015: Highlights of mathematics and science achievement of grade 9 South African learners. Human Sciences Research Council.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/doi: 10.1037//0003-066X.55.1.68
Sarioglan, A. B., & Can, Y. (2021). Effect of Open Inquiry Based Learning Approach on the Conceptual Understanding of Secondary School Students. International Online Journal of Educational Sciences, 13(2). https://doi.org/10.15345/iojes.2021.02.007
Savery, J. R. (2019). Comparative pedagogical models of problem‐based learning. The Wiley Handbook of Problem‐based Learning, 81–104.
Stott, A. E., & Beelders, T. (2019). The influence of science reading comprehension on South African township learners’ learning of science. South African Journal of Science, 115(1–2), 72–80. https://doi.org/https://doi.org/10.17159/sajs.2019/5146
Stott, A. E., & Duvenhage, M. (2023). The Response of Higher-Achieving South African Learners from Poverty to an Extracurricular Mathematics-guided Problem-based Learning Programme. African Journal of Research in Mathematics, Science and Technology Education, 1–14. https://doi.org/10.1080/18117295.2023.2275857
Taylor, D. (2011). ‘They are using laptops, we are using boxes’: township learners’ conceptions of Expo. African Journal of Research in Mathematics, Science and Technology Education, 15(1), 67–79.
Van der Berg, S., Spaull, N., Wills, G., Gustafsson, M., & Kotzé, J. (2016). Identifying Binding Constraints in Education. In Research on Socio-Economic Policy. Department of Economics, University of Stellenbosch.
Van der Kaap-Deeder, J., Soenens, B., Ryan, R. M., & Vansteenkiste, M. (2020). Manual of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSNF). Ghent University, Belgium.
Wang, H. H., Hong, Z. R., She, H. C., Smith, T. J., Fielding, J., & Lin, H. shyang. (2022). The role of structured inquiry, open inquiry, and epistemological beliefs in developing secondary students’ scientific and mathematical literacies. International Journal of STEM Education, 9(1). https://doi.org/10.1186/s40594-022-00329-z
Zion, M., Schwartz, R. S., Rimerman-Shmueli, E., & Adler, I. (2020). Supporting Teachers’ Understanding of Nature of Science and Inquiry Through Personal Experience and Perception of Inquiry as a Dynamic Process. Research in Science Education, 50(4), 1281–1304. https://doi.org/10.1007/s11165-018-9732-9

No competing interests reported.

Download PDF

Reviews received at journal
03 Oct, 2024
Reviewers agreed at journal
01 Oct, 2024
Reviews received at journal
12 Sep, 2024
Reviewers agreed at journal
05 Sep, 2024
Reviewers invited by journal
04 Sep, 2024
Editor assigned by journal
04 Sep, 2024
Submission checks completed at journal
03 Sep, 2024
First submitted to journal
21 Aug, 2024

You are reading this latest preprint version

The advisability of science fair project topic origins: a case study of learners from disadvantaged backgrounds

Status:

Version 1

Abstract

Figures

Introduction

Research questions

Theoretical referents

The four paradigms of learning and instructional design

Basic Psychological Need Satisfaction (BPNS)

Method

Sample

Intervention

Data collection

Data analysis

Findings

All groups perceived the process positively, with slight differences between the groups

Projects with more teacher topic input tended to be of higher quality

The facilitator perceived the groups differently regarding output per input

Discussion

Limitations and suggestions for further investigation

Suggestions for practice: The Instruct-Expose-Explore-Formalise Framework

Declarations

Author Contribution

Data Availability

References

Additional Declarations

Status:

Version 1