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Article

Same Classroom, Different Reality: Secondary School Students’ Perceptions of STEM Lessons—A Pioneering Study

by
Lukas Ketscher
1,*,
Heidrun Stoeger
2,
Wilma Vialle
3 and
Albert Ziegler
1
1
Faculty of Humanities, Social Sciences, and Theology, Friedrich-Alexander-University of Erlangen-Nürnberg, 91054 Erlangen, Germany
2
Faculty of Human Sciences, University of Regensburg, 93053 Regensburg, Germany
3
School of Education, University of Wollongong, Wollongong, NSW 2500, Australia
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(4), 467; https://doi.org/10.3390/educsci15040467
Submission received: 22 February 2025 / Revised: 31 March 2025 / Accepted: 5 April 2025 / Published: 8 April 2025
(This article belongs to the Special Issue Innovative Approaches to Understanding Student Learning)
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Abstract

:
Our study is the first exploration of students’ situational perceptions of STEM lessons based on the DIAMONDS approach. This approach postulates eight perceptual dimensions: Duty, Intellect, Adversity, Mating, pOsitivity, Negativity, Deception, and Sociality. Three research questions were investigated in a validation study involving 447 eighth graders, each based on a distinct validation strategy. (1) Convergent validation strategy: How do students perceive STEM lessons regarding the DIAMONDS dimensions? (2) Criterion-related validation strategy: Are these perceptions associated with STEM education outcomes? (3) Explanatory validation strategy: Do gender differences also appear in the perception of STEM lessons? Data were collected via an online questionnaire. The main results indicated that (1) students associate STEM lessons mainly with Duty and Intellect; (2) their situational perception of STEM lessons was linked to STEM education outcomes; and (3) there were substantial variances in how students perceive STEM lessons. Male students perceived STEM lessons more positively (pOsitivity), while females associated them relatively more with negative attributes (Adversity, Negativity, or Deception). All three validation strategies produced results confirming the validity of the DIAMONDS approach. In this way, the results of our study offer a promising start for the DIAMONDS approach in STEM education research.

1. Introduction

In many countries, STEM (science, technology, engineering, and mathematics) has become a problem sector due to the lack of personnel. The reasons for this are complex and lie at various systemic levels. At an individual level, the causes are often found early in the individual’s development (Miller et al., 2024). STEM specializations or profiles, for example, are chosen less frequently than other subjects at school (e.g., Jansen et al., 2021). This continues in higher education. The largest proportion of STEM students in OECD countries is 36% in Germany. In the United States, the proportion is only 20%, and in Norway, the OECD country with the lowest proportion, it is 16% (OECD, 2024). In Germany, the STEM skills gap was estimated at 285,800 in 2023 (Anger et al., 2023), whereas in the United States, it is estimated to be around one million (Xue & Larson, 2015; Zaza et al., 2020).
Experts agree that attracting more people to STEM fields requires a multifaceted approach on multiple systemic levels (Sáinz et al., 2022; Xie et al., 2015). In recent years, research on designing an attractive and inviting STEM environment has increasingly focused on environmental cues. According to Cheryan et al. (2009), environmental cues are features of an environment that signal who belongs in that environment and can either include or exclude persons based on these signals. For instance, the physical decor in classrooms, offices, or workplaces can send implicit messages about the types of people expected or welcome in those spaces. Several studies have confirmed the role of factors in educational outcome variables, such as interest and a sense of (ambient) belonging (e.g., Cheryan et al., 2011, 2015) or participation in lessons (e.g., Muenks et al., 2020).
Approaches based on situational perception are a further development of the cue approach. Their two core ideas are that cues must first pass through a subjective perception. Therefore, a cue does not have a direct effect, leading to considerable inter-individual differences in the reaction to cues. The second core idea is that the ensemble of cues, or their holistic integration, is decisive in assessing a situation. Integrating such situational approaches into educational contexts, as Funder (2009, 2016) has earlier suggested, may have many benefits. Indeed, in recent years, a growing number of researchers have included situational perceptions of the educational context of various samples in their work, including teachers (Abrahams et al., 2021, 2024), adolescents (Konaszewski et al., 2025), and (university) students (Witte et al., 2024).

2. Theoretical Framework

For a long time, the dominant practice was to analyze objective aspects of a situation, such as who, what, when, and where (e.g., Parrigon et al., 2017; Pervin, 1978; Rauthmann et al., 2014; Saucier et al., 2007). However, considerable progress has recently been made towards a more holistic understanding of situations (e.g., Gerpott et al., 2018; Hoppler et al., 2021). Several taxonomies of situations have been proposed based on various approaches (e.g., Edwards & Templeton, 2005; Parrigon et al., 2017; Rauthmann et al., 2014). The DIAMONDS approach by Rauthmann et al. (2014) appears to be an emerging framework for analyzing situational perception in STEM lessons. Its main appeal is that it conceptually combines personal perception of a situation with its psychological appraisal, thus connecting it to behavioral outcomes. Furthermore, it has already proven fruitful in educational contexts (e.g., Abrahams et al., 2021, 2024; Konaszewski et al., 2025; Witte et al., 2024).
Using the Riverside-Situational-Q-Sort (RSQ) (e.g., Funder, 2016; Sauerberger & Funder, 2020; Wagerman & Funder, 2009), Rauthmann et al. (2014) found that people’s psychological appraisal of a situation is based on eight dimensions. Their initial or second letters form the acronym DIAMONDS: (1) The dimension of Duty is often associated with work and the fulfillment of duties (‘Does something need to be done?’). Duty is task-oriented and usually effortful. It is typically associated with cues related to working, studying, and exams. A positive correlation has been observed between Duty and conscientiousness. (2) In situations characterized by high levels of Intellect, individuals perceive cognitive demand or intellectual engagement (‘Is deep thinking required?’). In a manner analogous to Duty, Intellect appears to be of substantial importance within the perception of educational contexts (e.g., Konaszewski et al., 2025; Witte et al., 2024). A positive correlation has been observed between Intellect and openness. (3) Situations associated with Adversity are characterized by conflict, criticism, and victimization (‘Is someone threatened?’) (Parrigon et al., 2017). (4) The dimension of Mating is associated with situations conducive to romance, including the making of a positive impression on potential and actual mates (‘Is the situation sexually or romantically charged?’). As such, the dimension of Mating is a social dimension, but some authors also see it as a “basic evolutionary motif” (Kesberg & Keller, 2018, p. 4). The dimension of Mating has been demonstrated to exhibit a negative correlation with cues of working, studying, or goal affordances of intellect and growth (e.g., education). Conversely, a positive correlation has been observed between Mating and social relations (e.g., social recognition). (5) The dimension of pOsitivity is linked to positive characteristics of a situation (e.g., enjoyable, easy-to-navigate) (‘Is the situation [or aspects of it] pleasant?’). (6) In contrast, the dimension of Negativity is associated with situational factors of negative valence (e.g., anger) (‘Can negative feelings ensue?’). Negativity and pOsitivity are independent constructs and, therefore, do not represent the two poles of a continuum. Consequently, this enables both the positive and negative aspects of a given situation to be captured. (7) Deception is a negatively connoted dimension of situations associated with mistrust and lies (‘Are there issues of [mis-]trust?’). It is often associated with events such as exams and locations like universities and schools. (8) The dimension of Sociality is associated with factors such as communication and interaction (‘Is social interaction present or important?’). For Mating, it is thus a social dimension.
The DIAMONDS approach has been successfully employed in various situational analyses, including everyday life and music (Behbehani & Steffens, 2021). It has also been applied in various educational settings (e.g., Abrahams et al., 2021, 2024; Konaszewski et al., 2025; Witte et al., 2024); however, its application in the context of STEM education has not yet been explored.
In STEM education research, a situational approach appears particularly promising as a complement to existing approaches. First, it has the potential to bridge distal and proximal explanatory variables. Traditional approaches to explaining STEM learning and career choices often focus on distal variables, such as socioeconomic background and societal stereotypes, or proximal variables, including momentary engagement and classroom interactions (Archer et al., 2015; Stoeger et al., 2024). The DIAMONDS approach provides a framework that accounts for distal and proximal factors in a situation’s perception and psychological appraisal (Rauthmann et al., 2014), such as learning in a STEM classroom. Second, situational contextualization of individual differences theories in STEM education research (Chen & Simpson, 2015) assumes that situations dynamically interact with personal attributes (Rauthmann et al., 2014). One often-cited example is the phenomenon of a stereotype threat, in which personal attributes become salient in a particular situation and can negatively impact performance in STEM fields (Seo & Lee, 2021). Third, several research methodologies, such as quantitative, qualitative, and mixed methods, have proven fruitful in STEM education research. However, it is often difficult to relate their data to each other. The concept of the situation can provide a framework that aligns measurable, quantitative patterns with lived, qualitative, real-time, and context-sensitive experiences. Fourth, many approaches in STEM education research implicitly assume linear pathways from learning to learning outcomes or interest to career choices (e.g., Han et al., 2021). The DIAMONDS approach opens up the possibility of situational variability by incorporating subjectively perceived factors such as the classroom climate, peer influences, and unexpected difficulties in coursework. Fifth, the DIAMONDS approach provides a framework for fine-tuning STEM education to immediate contextual variables, thereby improving its effectiveness in real classrooms and informal STEM settings. Taken together, these potential advantages make a situational approach in STEM education research appear promising. Our overarching aim, therefore, is to conduct a pioneering study to obtain initial evidence for this assumption.

3. The Present Study

The present study was designed to validate the DIAMONDS approach in STEM education research. We pursued three research questions, each based on a different validation strategy. In RQ1, convergent validation (Creswell & Plano Clark, 2018) indicates the extent to which the situational perceptions of STEM education align with those from comparable studies in similar contexts. RQ2 examines the criterion-related validity, i.e., the concurrent validity of the DIAMONDS dimensions in relation to the desired outcomes of STEM education. RQ3 aimed to establish explanatory validity, specifically investigating whether the DIAMONDS approach can contribute to explaining a phenomenon that is still not fully understood (Franck, 2002) in the present case of gender differences in STEM education.
In line with previous research in educational settings, we formed two expectations. First, we expected the two dimensions, Duty and Intellect, to be particularly pronounced in the situational perception of STEM teaching (cf. Konaszewski et al., 2025; Roemer et al., 2021; Witte et al., 2024). Second, we expected a high variance in perceptions of the DIAMONDS dimensions in STEM classes (cf. Rauthmann et al., 2014, for a general overview based on everyday situations).
  • RQ2: How are situational perceptions related to outcomes of STEM education?
Our study investigated the relationship between the DIAMONDS dimensions and various desirable outcomes in STEM education. Specifically, these included a sense of belonging to the STEM class community, task values in STEM domains, confidence in STEM abilities, career security, participation in STEM-related activities, and intentions to pursue STEM career electives. In line with previous research (Roemer et al., 2021; Witte et al., 2024), we expected that perceiving STEM education in a way that evokes the DIAMONDS of Duty and Intellect would be associated with the desired outcomes of STEM education. We also expected the two DIAMONDS, which describe the valences of a situation, to correlate positively (i.e., pOsitivity) or negatively (i.e., Negativity) with desired STEM outcomes (cf. Cheryan et al., 2009, 2011, 2015). A plethora of studies have identified positive correlations between social factors such as the classroom climate (Wang et al., 2020), social support (Rosenfeld et al., 2000), social embeddedness (Harks & Hannover, 2020), and sense of belonging. Thus, we would expect a positive correlation between the dimension of Sociality and a sense of belonging to the STEM class community. We had no clear expectations for the DIAMONDS dimensions of Adversity, Mating, and Deception. However, if significant correlational patterns emerge, we would expect the latter two dimensions to correlate with undesired outcomes of STEM education.
  • RQ3: Do boys and girls differ in their situational perception of STEM lessons?
A substantial body of research has been dedicated to the subject of gender differences in STEM (Mullet et al., 2017; Wang & Degol, 2017). Typically, less favorable results are found for girls. This would imply that gender differences should also be evident in the situational perception of STEM education. Indeed, Leiner et al. (2018) demonstrated gender differences in the perception of high-stakes test situations; however, more recent results focusing on STEM education reveal more nuanced findings. For example, the results of Fairhurst et al. (2023) showed no significant differences in the characteristics of Collaboration and Challenge. This suggests that similar tendencies can also be expected for the DIAMONDS dimensions with social components (i.e., Mating, Sociality) and overcoming difficulties (i.e., Intellect). Beyond that, however, girls are expected to show less positive values in the other DIAMONDS dimensions, especially with regard to Negativity.

4. Method

4.1. Procedure

The data collection took place in eleven schools across several German federal states, including Bavaria, Lower Saxony, and Hesse. Before participation, explicit consent was obtained from the students and their legal guardians. The students completed an online questionnaire. To ensure the consistency of the survey process, STEM coordinators and teachers at the participating schools were provided with detailed written instructions and asked to administer the survey within the school’s IT facilities.

4.2. Sample

Participants in our study were 521 eighth-grade students in secondary school (nmale = 224, nfemale = 275, nother = 14, nnot spezified = 8). After removal of students with a largely incomplete dataset and unspecified gender, as well as further steps in the data cleaning process, the final sample consisted of N = 447 students (MAge = 13.75 years; SDAge = 0.43), of which 188 identified themselves as male (MAge_male = 13.79 years; SDAge_male = 0.39) and 259 as female (MAge_female = 13.71 years; SDAge_female = 0.46).

4.3. Measures

As part of the study, basic demographic data, including gender and age, were first recorded.
Situation Perception. We used the DIAMONDS S8-1 scale by Rauthmann and Sherman (2018) to measure situation perception. The scale is based on the theoretical work of Rauthmann et al. (2014) and Rauthmann and Sherman (2016a, 2016b) on situation perception. Each of the DIAMONDS is measured with one item. To align with the research focus, we made adaptations to STEM education, for example, by adding the phrase “in STEM lessons” to the original items (e.g., “I feel comfortable in STEM lessons”, “I have negative feelings [e.g., stress, anxiety, guilt, etc.] in STEM lessons”, “I often feel deceived in STEM lessons”). Each item was assessed on a 7-point Likert-type scale ranging from 1 = not at all to 7 = totally.
Sense of belonging to the STEM class community. We measured the sense of belonging to the STEM class community with a four-item scale by O’Keeffe (2013). The items were adapted to the STEM field. A sample item is “I do not belong to my STEM class”. Answers were given on a six-point Likert-type scale ranging from 1 = not at all true to 6 = completely true. After omitting one item, the reliability was κ = 0.87.
Task values in STEM domains. We used a scale based on Gaspard et al. (2015) to assess the intrinsic (two items), attainment (two items), and utility value (two items) of STEM with a single six-point Likert-Scale ranging from 1 = not at all true to 6 = completely true. The subscales were subsequently summarized into an overall scale (Task values in STEM domains). A sample item is “STEM is very important to me personally”. The reliability was κ = 0.89.
Confidence in one’s STEM abilities. This construct was measured using a four-item scale by Stoeger et al. (2013), which was based on Dweck’s (1999) scale of belief in one’s own abilities. The endpoints of the six-point scale were formulated as statements, e.g., “I do not have a great deal of confidence in my STEM abilities” vs. “I am confident in my STEM abilities”. A lower score on this six-point rating scale represented low confidence in STEM skills. The reliability was κ = 0.91.
Certainty in career orientation. To measure certainty in career orientation, we used the sub-scale Certainty/Decisiveness of the Attitude Scale of the Career Maturity Inventory (Seifert & Stangl, 1986), which measures the general sense of security in career orientation. The scale consists of six items on a six-point Likert scale ranging from 1 = not at all true to 6 = completely true. A sample item is “I don’t know what I should do to choose the best profession”. The reliability was κ = 0.85.
STEM-related activities. STEM-related activities were measured with an eleven-item scale by Stoeger et al. (2013). It measures the extent to which students engage in STEM-related activities in their daily lives. These include reading books with STEM content, talking about STEM in everyday life, and visiting STEM exhibitions. The response options ranged from 1 = not at all true to 6 = completely true. The reliability was κ = 0.89.
STEM career elective intentions. This scale, developed by Stoeger et al. (2013), consists of six items on a six-point Likert scale from 1 = not at all true to 6 = completely true to measure the extent to which students aspire to a career in STEM. A sample item reads, “I can picture myself studying a STEM subject at university”. The reliability was κ = 0.89.

4.4. Data Analysis

The results were analyzed using SPSS Version 29.0.2.0 (IBM Corp, 2023) and R Version 4.3.0 (R Core Team, 2023). Only the data that had successfully undergone a data cleansing process was taken into consideration. This process entailed the following steps: (a) ensuring that educational institutions possessed the requisite consent forms for the collection and processing of data on all students surveyed; (b) identifying datasets that exhibited response patterns or contained nonsensical information in the user-defined text box; and (c) assessing the reliability of the scales to permit further processing of the data.
As Kolmogorov–Smirnov and Shapiro–Wilk tests indicated that none of the dimensions of the DIAMONDS were normally distributed, we decided to apply non-parametric methods. In the following analysis, differences between the dimensions were examined using the Wilcoxon signed-rank test (RQ1), correlations were analyzed using Spearman’s rank correlation (RQ2), and gender differences were calculated using the Mann–Whitney U-test (RQ3).

5. Results

RQ1 asked how students perceive STEM lessons based on the eight DIAMONDS dimensions. We expected that Duty and Intellect would predominate in their mean values. Table 1 presents the mean values and standard deviations for the total group, as well as the results of the Wilcoxon signed-rank test for individual dimensions. Indeed, as anticipated, Duty (M = 4.85; SD = 1.53) and Intellect (M = 4.85; SD = 1.51) were found to be predominant.
We expected relatively high standard deviations. Though there is no generally accepted convention when a standard deviation on a Likert scale is considered ‘high’, our findings of standard deviations ranging from Intellect = 1.51 to Mating = 1.98 confirm our hypothesis (see Figure 1). Consider this thought experiment. The standard deviations of all DIAMONDS are over 1.5 on the 7-point Likert scale. For a normally distributed variable with an M = 4, i.e., precisely on the mean of the scale, around 32% of the values lie outside the range of 2.5 and 5.5. Another interesting aspect is that only one of the DIAMONDS has a mean value within a third of a standard deviation of the theoretical scale mean (MDeception = Mtheoretical − 0.32 SD). Four of the DIAMONDS are above, and four are below the theoretical scale mean. The less characterizing DIAMONDS, i.e., those below the theoretical scale mean, include the three negative DIAMONDS of Adversity, Negativity, and Deception. Since pOsitivity and Sociality are among the more strongly perceived DIAMONDS, i.e., above the theoretical scale mean, the overall perception of STEM teaching can be assessed as favorable. If only the mean values of the eight DIAMONDS are considered, a distinctive perception profile of STEM lessons emerges. Four mean values were at least about one-third of a standard deviation or more above the theoretical scale mean (Duty, Intellect, pOsitivity, and Sociality), and four mean values were at least about one-third of a standard deviation or more below the theoretical scale mean (Adversity, Mating, Negativity, and Deception).
In summary, our expectations regarding RQ1 were confirmed. The two dimensions, Duty and Intellect, were particularly pronounced, and the variances in the perceptions of the DIAMONDS dimensions in STEM classes were large. Our convergent validation strategy thus yielded a first promising result.
With RQ2, we aimed to determine whether situational perceptions are associated with STEM education outcomes, including a sense of belonging to the STEM class community, task values in STEM domains, confidence in one’s STEM abilities, certainty in career orientation, participation in STEM-related activities, and intentions to pursue STEM careers in an elective setting. Table 2 shows all correlations between the DIAMONDS and these validation variables.
We identified four significant correlations related to a sense of belonging within the STEM class community. As expected, the negative perception (Negativity) correlated negatively with a sense of belonging to the STEM class community, while we found a positive correlation with pOsitivity. Notably, dimensions with negative connotations, such as Adversity and Deception, continue to demonstrate negative correlations. Therefore, this correlation pattern is plausible, and we regard it as a validation of the DIAMONDS.
Table 2 also shows significant correlations between task values in the STEM domains and all eight DIAMONDS. This correlation pattern is also plausible, as, on the one hand, only the negative perceptions correlated negatively with the task values in the STEM domains (Adversity, Negativity, and Deception). All other correlations were positive, with pOsitivity standing out due to its magnitude. Thus, we consider this correlation pattern also to be a validation of DIAMONDS.
Regarding confidence in one’s own STEM ability, two negative correlations were found with the negative perceptions of STEM lessons (Negativity and Deception). In contrast, the more positive perceptions of pOsitivity and Sociality were positively correlated with confidence in one’s own STEM ability. This correlation pattern is considered to validate the DIAMONDS approach in the context of STEM education.
The negative perceptual dimensions of STEM lessons, namely Adversity, Negativity, and Deception, were significantly negatively correlated with the security of career orientation. No other correlations exceeded the set significance level. However, we consider the result plausible and, therefore, a validation of the DIAMONDS.
The correlation pattern between the DIAMONDS and participation in STEM-related activities deviated somewhat from the previous correlation patterns. Significant negative correlations were not found with the negative perceptions of Adversity, Negativity, and Deception. Five significant positive correlations were found (e.g., with Duty, Intellect, pOsitivity, and Sociality), with pOsitivity correlating most strongly. Interestingly, there are also correlations with Mating, i.e., STEM-related activities appear as opportunities where it is important to make a positive impression on potential and actual mates. Despite the absence of significant negative connotations, this correlation pattern is plausible.
Six of the eight DIAMONDS correlate significantly with STEM career elective intentions. Similar to the correlational pattern with STEM-related activities, weak negative correlations were found between the two negative perceptions of Negativity and Deception, but no significant correlation was found with Adversity. Again, multiple significant positive correlations emerged (e.g., with Duty, pOsitivity, and Sociality), with pOsitivity again correlating most strongly.
To summarize: In addressing RQ2, we employed a criterion-related validation strategy. In accordance with the DIAMONDS framework, expectations were formulated regarding the correlations between the dimensions and desired and undesired outcomes of the criterion variables. In general, these expectations were confirmed. We, therefore, consider the results of our second validation strategy to be promising, as well.
RQ3 addressed gender differences regarding the situation perception of STEM lessons. We expected no significant differences in Intellect and the social dimensions (i.e., Mating and Sociality). Furthermore, the assumption is that male students exhibit a more positive perception of STEM lessons than their female counterparts. Table 3 presents the results of the Mann–Whitney U tests, which generally align with expectations. No significant differences were identified for Intellect (U = 21,377.50; Z = −1.70; p = 0.090) and Sociality (U = 22,447.00; Z = −0.75; p = 0.456). As anticipated, the study found that girls exhibited a heightened perception of the three dimensions with a negative connotation. Therefore, Negativity (U = 17,770.00; Z = −4.40; p < 0.001), Deception (U = 18,980.00; Z = −3.46; p < 0.001), and Adversity (U = 20,355.00; Z = −2.51; p = 0.012) were more strongly perceived in STEM lessons by female students than males. Although Duty (U = 20,950.00; Z = −2.04; p = 0.041) and Intellect (U = 21,377.50; Z = −1.70; p = 0.090) do have higher mean value ratings by female students, the differences were only statistically significant regarding Duty. Boys perceived higher pOsitivity (U = 20,271.00; Z = −2.47; p = 0.014). Interestingly, girls were also slightly more likely to perceive STEM lessons as an opportunity to form romantic relationships (U = 20,502.50; Z = −2.33; p = 0.020). In conclusion, the overall rating of the boys’ situational perception of STEM lessons is that it is more positive. Furthermore, considering the plausible patterns for Intellect and Sociality, the results obtained are generally interpreted as validation of the DIAMONDS in relation to STEM education.
To summarize, in the case of RQ3, we employed an explanatory validation strategy. We examined whether the gender differences in STEM reported in many studies are also reflected in boys’ more favorable perceptions of STEM classrooms, which was the case. Therefore, this validation strategy also yielded promising results.

6. Discussion

A long-standing desideratum has been a better understanding of situations and their characteristics in education (Funder, 2009, 2016). This paper contributes to the research literature on STEM education by employing the DIAMONDS approach (Rauthmann et al., 2014) for the first time, thereby establishing a research foundation for studying situation perception in STEM education. We pursued three research questions, each based on a different validation strategy. First, applying a convergent validation strategy, we were interested in how students perceive STEM lessons in relation to the dimensions postulated in the DIAMONDS approach. Second, to criterion validating the DIAMONDS approach in STEM education, we wanted to find out whether the DIAMONDS are associated with a wide range of STEM education outcomes (i.e., a sense of belonging to a STEM class community, task values in STEM domains, confidence in one’s STEM abilities, certainty in career orientation, STEM-related activities, and STEM careers elective intentions). Finally, aiming to establish explanatory validity, we wanted to know whether the gender differences widely reported in STEM (Mullet et al., 2017; Wang & Degol, 2017) are also reflected in the perceptions of STEM classrooms.
In relation to RQ1, STEM lessons are generally perceived positively overall. However, this assessment is subject to two caveats. It must also be taken into account that although a negative perception is below the scale mean, its impact can be severe. For example, on a 7-point scale ranging from 1 = not at all to 7 = totally, the students in our study perceived, on average, at 3.45 that they could be deceived in a STEM lesson, which seems relatively high. From a pedagogical perspective, our study’s results provide constructive starting points for STEM education, as a largely positive image of STEM lessons can be built upon. On the other hand, there are also worrying perceptions, the exact effects of which need to be investigated, for example, concerning Negativity and Deception. Suppose these perceptions are based on situational facts and reflect not only subjective perceptions; objective conditions must be addressed. Thus, further research is necessary to ascertain the extent to which these negatively connoted dimensions are associated with individual environmental cues (e.g., wall decor) (e.g., Cheryan et al., 2009, 2011, 2015), the impact of other persons (e.g., disruptive behavior) (e.g., Guardino & Fullerton, 2010), or, e.g., the didactic implementation of instruction in the form of deliberate practice, which is occasionally perceived as aversive by individual students (Stoeger et al., 2024). However, the DIAMONDS approach clarifies that this will not be enough. Objective improvements also require their unbiased perception, for example, by reducing mistrust and negative stereotypes (Aronson & Steele, 2005; Estrada et al., 2016; Van Maele et al., 2014).
Regarding RQ2, the present study found numerous correlations between the DIAMONDS and the outcome variables. Except for the dimension of Mating, which is unclear regarding adaptability to STEM education, the remaining dimensions are interpretable. Positive perceptions of the two social DIAMONDS of Mating and Sociality tend to be associated with more positive STEM education outcomes. This is no surprise for Sociality, as social factors have been associated with positive STEM education outcomes in numerous studies (Harks & Hannover, 2020; Rosenfeld et al., 2000; Wang et al., 2020). However, the correlational pattern for Mating is somewhat unexpected in light of the previous findings (see Kesberg & Keller, 2018). Furthermore, thirteen of the eighteen correlations between the negative connoted dimensions (i.e., Negativity, Deception, and Adversity) and the criterion variables were, as expected, significantly correlated with undesired STEM education outcomes. Among these five non-significant correlations, three included the DIAMONDS dimension of Adversity. Indeed, there is some controversy in the research literature regarding whether the concept of Adversity or a labeling/conceptualization as Antagonism, as proposed by Parrigon et al. (2017), better represents this dimension and leads to a more plausible correlation pattern. We suggest that in subsequent research, the scope should be expanded to encompass additional dimensions, such as Antagonism or Typicality (e.g., Abrahams et al., 2021; Witte et al., 2024; for a more detailed discussion of situational dimensions, see Kuper et al., 2022, 2024).
RQ3 referred to gender differences in STEM, which have been documented in numerous studies (Mullet et al., 2017; Wang & Degol, 2017). It was interesting to see whether they could also be reproduced at the level of situational perception. By and large, we expected boys to have more positive values. Our findings indeed confirm this expectation. Girls have significantly higher values than boys for the three negative situational perceptions of Adversity, Negativity, and Deception, and lower values for pOsitivity. The prevailing suggestion is that these gender-specific differences are attributable to the perception of environmental cues, such as the room decor. As assumed, there was no significant difference in Intellect and Sociality. However, caution is required here. Girls showed higher values in our study regarding Duty (as Kesberg and Keller (2018) have previously loosely intimated) and Intellect. Since there is a possibility that our study was underpowered, we do not want to rule out the possibility that girls had (significantly) higher scores on these two dimensions.
Overall, the results of our study are encouraging, suggesting further investigation into situational perceptions in STEM education. The DIAMONDS approach has the potential to trigger a plethora of research questions. One part of this will be re-examining already established research questions through the lenses of the DIAMONDS approach. We want to provide a concrete research example of this with the role of attributional style and an example of how analyzing situations rather than more distal constructs potentially broadly influences research outcomes in STEM education.
Numerous research studies have shown that students’ attributional style impacts their cognitions, emotions, motivations, and behavior (Weiner, 2010). However, research also indicates that attributions in STEM can be modified by situational influences, such as priming (Bedyńska et al., 2018), emotional state and stress (Lu et al., 2023), or the immediate social environment (McLure et al., 2022; Seo & Lee, 2021). Since the DIAMONDS provide an elaborate and well-validated framework for understanding situational perceptions, it would be interesting to see how they influence attributions. The same applies to all other variables that situational influences can modify. However, zooming into situations also has other fundamental consequences for research. For example, people’s response behavior depends on the temporal distance between events. Trope and Liberman (2003) showed that the greater the temporal distance to an event, the more likely it is to be depicted using abstract characteristics limited to its essence. The extent to which this applies to findings from STEM education research when focusing more on situations is an exciting future research question.
Finally, we would like to identify two further essential research questions that should be investigated from the perspective of situational perception in the future. Our study on situation perception, based on the DIAMONDS approach, used STEM as the investigative unit. However, research also shows differences between the STEM subjects (Varas, 2016; Wang & Degol, 2017). Therefore, the extent to which a finer differentiation should be made between STEM subjects should be investigated. The second important research question concerns equity gaps, which have been demonstrated in numerous types between multiple groups in STEM (Vinni-Laakso et al., 2022; Ziegler & Stoeger, 2023). With situational perception gaps, our research suggests the existence of a potentially new class of proximal equity gaps. As they are localized at the interface between person and environment, they may offer interesting potential for intervention.

7. Conclusions

In this paper, we have presented arguments that a situational approach can be potentially fruitful for STEM education research. These include the potential to connect distal and proximal explanatory variables as well as provide a framework that aligns measurable, quantitative patterns with qualitative and context-sensitive experiences.
The DIAMONDS framework appears to be particularly suitable as it has already been successfully applied in educational research. However, an empirical study in the field of STEM education has not yet been conducted. In our pioneering study, we used three validation strategies that have yielded promising results. This invites further research, in which the range of methods, however, needs to be substantially expanded. In particular, qualitative and mixed-method studies have the potential to offer a more comprehensive understanding.
To date, the DIAMONDS framework has not been implemented within the context of STEM educational practice. However, should further research corroborate its explanatory strength for STEM educational outcomes, the development of practical implementations will become an urgent pedagogical desideratum.

Author Contributions

Conceptualization, A.Z., H.S. and L.K.; methodology, A.Z. and L.K.; software, L.K.; data analysis, A.Z. and L.K.; investigation, A.Z., H.S. and L.K.; data collection, A.Z., H.S., L.K; writing—original draft preparation, A.Z. and L.K.; writing—review and editing, A.Z., H.S., L.K. and W.V.; visualization, L.K.; supervision, A.Z.; translation, W.V. All authors have read and agreed to the published version of the manuscript.

Funding

The authors declare that the research was supported by the German Federal Ministry of Education and Research (BMBF) under project grant number 16MF1091B.

Institutional Review Board Statement

Ethical review and approval by an ethic committee was not required for the study on human participants in accordance with the local legislation and institutional requirements. Our concept for protecting participants’ data was in accordance with national standards and was approved by the participating institutions (e.g., ministries of participating German states and the principals of participating schools).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. As the survey was conducted on underage students, the consent of their legal guardians was also obtained.

Data Availability Statement

The datasets presented in this article are not readily available as the project will run until 2027. The data will be made available in anonymized form at the end of the funded project.

Acknowledgments

This publication resulted from the joint project “FösaMINT—Förderung schulisch-außerschulischer MINT-Kooperation mit Genderschwerpunkt“. The project is funded by the Federal Ministry of Education and Research (BMBF) under the project grant number 16MF1091B. The following institutions participated in the study as practice partners: Deutsche Telekom Stiftung, Körber-Stiftung. The responsibility for the content of this publication lies with the authors.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

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Education 15 00467 g001
Figure 1. Graphical representation of the means and standard deviations of the DIAMONDS for the total group.
Figure 1. Graphical representation of the means and standard deviations of the DIAMONDS for the total group.
Education 15 00467 g001
Table 1. Means and standard deviations of the DIAMONDS for the total group and the genders. Superscripts indicate the results of the Wilcoxon signed-rank tests comparing the mean values of DIAMONDS across the total group.
Table 1. Means and standard deviations of the DIAMONDS for the total group and the genders. Superscripts indicate the results of the Wilcoxon signed-rank tests comparing the mean values of DIAMONDS across the total group.
DimensionTotal Mean (SD)Gender
Male Mean (SD)Female Mean (SD)
Duty a4.85 (1.53)4.64 (1.65)5.00 (1.42)
Intellect a4.85 (1.51)4.71 (1.55)4.95 (1.47)
Adversity e2.59 (1.63)2.40 (1.65)2.73 (1.60)
Mating d2.87 (1.98)2.60 (1.88)3.07 (2.03)
pOsitivity b4.56 (1.58)4.77 (1.61)4.41 (1.55)
Negativity d3.02 (1.75)2.61 (1.66)3.32 (1.75)
Deception c3.45 (1.73)3.12 (1.71)3.69 (1.70)
Sociality b4.60 (1.56)4.67 (1.63)4.54 (1.51)
Note. Identical superscripts indicate that two DIAMONDS do not differ significantly, p > 0.01.
Table 2. Spearman’s rank correlation between perceptions of STEM lessons and validation variables.
Table 2. Spearman’s rank correlation between perceptions of STEM lessons and validation variables.
DimensionSense of Belonging to the STEM Class CommunityTask Values in STEM DomainsConfidence in STEM AbilitySecurity in Career OrientationSTEM-Related ActivitiesSTEM Career
Elective Intentions
Duty0.040.30 ***0.080.000.25 ***0.21 ***
Intellect0.030.13 **−0.02−0.030.13 **0.08
Adversity−0.19 ***−0.12 *−0.08−0.15 **0.01−0.08
Mating−0.010.17 ***0.11 *0.060.25 ***0.18 ***
pOsitivity0.14 **0.59 ***0.46 ***0.090.32 ***0.51 ***
Negativity−0.22 ***−0.29 ***−0.38 ***−0.12 *−0.08−0.25 ***
Deception−0.22 ***−0.28 ***−0.29 ***−0.13 **−0.09−0.27 ***
Sociality0.070.26 ***0.11 *−0.060.17 ***0.21 ***
Note. Two-tailed correlations were considered. * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 3. Results of the Mann–Whitney U-test testing for gender differences.
Table 3. Results of the Mann–Whitney U-test testing for gender differences.
DimensionGroupMedianMean RankUZp
Dutymale4.00206.3620,950.00−2.04 *0.041
female5.00230.66
Intellectmale4.00208.6821,377.50−1.700.090
female5.00228.99
Adversitymale2.00203.1320,355.00−2.51 *0.012
female2.00232.99
Matingmale2.00204.0420,502.50−2.33 *0.020
female3.00231.41
pOsitivitymale5.00237.2320,271.00−2.47 *0.014
female4.00207.68
Negativitymale2.00189.1017,770.00−4.40 ***<0.001
female3.00242.09
Deceptionmale3.00195.7218,980.00−3.46 ***<0.001
female4.00237.36
Socialitymale4.00225.1722,447.00−0.750.456
female4.00216.30
Note. Two-tailed Mann–Whitney U-test probabilities. * p < 0.05, *** p < 0.001.
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Ketscher, L.; Stoeger, H.; Vialle, W.; Ziegler, A. Same Classroom, Different Reality: Secondary School Students’ Perceptions of STEM Lessons—A Pioneering Study. Educ. Sci. 2025, 15, 467. https://doi.org/10.3390/educsci15040467

AMA Style

Ketscher L, Stoeger H, Vialle W, Ziegler A. Same Classroom, Different Reality: Secondary School Students’ Perceptions of STEM Lessons—A Pioneering Study. Education Sciences. 2025; 15(4):467. https://doi.org/10.3390/educsci15040467

Chicago/Turabian Style

Ketscher, Lukas, Heidrun Stoeger, Wilma Vialle, and Albert Ziegler. 2025. "Same Classroom, Different Reality: Secondary School Students’ Perceptions of STEM Lessons—A Pioneering Study" Education Sciences 15, no. 4: 467. https://doi.org/10.3390/educsci15040467

APA Style

Ketscher, L., Stoeger, H., Vialle, W., & Ziegler, A. (2025). Same Classroom, Different Reality: Secondary School Students’ Perceptions of STEM Lessons—A Pioneering Study. Education Sciences, 15(4), 467. https://doi.org/10.3390/educsci15040467

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