Forma mentis networks reconstruct how Italian high schoolers and international STEM experts perceive teachers, students, scientists, and school
FForma mentis networks reconstruct how Italianhigh schoolers and international STEM expertsperceive teachers, students, scientists, and school
Massimo Stella Complex Science Consulting, Via Amilcare Foscarini 2, Lecce, Italy. Email:[email protected] 9, 2020
Abstract
This study investigates how students and researchers shape their knowledge and perceptionof educational topics. The mindset or forma mentis of 159 Italian high school students and of59 international researchers in science, technology, engineering and maths (STEM) are recon-structed through forma mentis networks, i.e., cognitive networks of concepts connected by freeassociations and enriched with sentiment labels. The layout of conceptual associations betweenpositively/negatively/neutrally perceived concepts is informative on how people build their ownmental constructs or beliefs about specific topics. Researchers displayed mixed positive/neutralmental representations of “teacher”, “student” and, “scientist”. Students’ conceptual associa-tions of “scientist” were highly positive and largely non-stereotypical, although links about the“mad scientist” stereotype persisted. Students perceived “teacher” as a complex figure, associatedwith positive aspects like mentoring/knowledge transmission but also to negative sides revolvingaround testing and grading. “School” elicited stronger differences between the two groups. In thestudents’ mindset, “school” was surrounded by a negative emotional aura or set of associations,indicating an anxious perception of the school setting, mixing scholastic concepts, anxiety-elicitingwords, STEM disciplines like maths and physics, and exam-related notions. Researchers’ positivestance of “school” included concepts of fun, friendship, and personal growth instead. Along theperspective of Education Research, the above results are discussed as quantitative evidence fortest- and STEM anxiety co-occurring in the way Italian students perceive education places andtheir actors. Detecting these patterns in student populations through forma mentis networks offersnew, simple to gather yet detailed knowledge for future data-informed intervention policies andaction research.
Keywords:
Complex networks; networks and education; cognitive network science; language mod-elling; cognition and language; STEM education; anxiety.
Increasingly more studies in Education Science suggest that a large number of students experience anx-iety while in educational settings [1, 2, 3, 4, 5]. Stress can arise from multiple sources. Among science,technology, engineering and mathematics (STEM) subjects, disciplines like physics [1], maths [3], andstatistics [5] are increasingly reported to elicit fearful emotional states of higher alertness across differ-ent educational systems and levels, from primary school to college students [3, 5]. This phenomenonwas first detected by Mallow, who also coined the term “science anxiety” [1], and then related it to poorperformance in science courses [1, 6, 3, 5]. The heightened state of arousal induced by anxiety ends upinhibiting students’ concentration on the task at end, importantly impacting problem solving [6] andeven knowledge retention [4]. Anxiety can originate from several sources in a given educational setting.Teachers’ behavior can greatly affect classroom settings, ultimately provoking alertness in students ei-ther through active [1] (e.g., using assessments in unbalanced ways) or passive behavior (e.g., neglectingpeer-learning or cooperative learning [7, 8]). Notice that personal assessment in Education is a ratherdelicate matter, with imminent examinations frequently inducing the so-called “test anxiety” [9, 2],a feeling of distress, over-arousal, and tension that is mostly detected before taking an exam or atest. Cassady and Johnson showed that moderate levels of anxiety correlated positively with betteracademic achievements whereas stronger levels of anxiety impacted negatively test performance [9].Importantly, science anxiety can arise also from a lack of role models and a generally dry perceptionof a subject [1]. Recurrent stereotypes of scientists in terms of “intelligent-yet-boring” individuals [10]or “evil geniuses” [11] provide a distorted picture of the nature of science and knowledge creation andprevent students from getting inspirational role models, which can ultimately help dealing with stressand improve personal academic achievement [12]. In psychology, stereotypes summarize common ex-pectations about the main features possessed by members of a given group [13]. Negative stereotypescan affect self-judgement, reduce working memory performance, elicit anxiety and drastically hinderacademic performance [13], a phenomenon known as stereotype threat and recently identified also inSTEM education [14]. It is important to underline that the development and exacerbation of anxious1 a r X i v : . [ phy s i c s . e d - ph ] J a n oods from all the above sources have detrimental effects for students’ performance within schoolsettings and beyond [6, 3, 5], decreasing academic achievement [1, 4] and preventing students frompursuing STEM careers [15]. Within this complex picture, it becomes of utmost importance to developgeneral and simple techniques quantifying and detecting anxiety in the students’ perception of theirclassroom settings, of STEM subjects, of potential stereotypes and, more in general, of the wholeeducational system.Forma mentis networks (FMN) were recently introduced by Stella and colleagues [16] and shownto be capable of detecting anxiety patterns through easily obtainable cognitive data. Building onthese results, this paper adopts the framework of forma mentis networks for better understandingthe perception toward educational topics and STEM of high school students in their final year ofstudies, with a focus on the Italian educational system. Being almost on the verge of graduation, thesestudents completed their career through primary education and most of secondary education and aretherefore representative of the learning outcomes of such systems. Mapping the students’ mindsetor forma mentis (in Latin) can shed light on particular anxiety-related, negative or positive stancesthat should be better investigated or acted upon by Education researchers, teaching professionals andpolicy makers for improving students’ experience and their academic impact in STEM.FMNs combine network science and cognitive science methods and data [16, 17] with the aimof stance detection, i.e., identifying whether an individual or a group is in favor or against a giventopic. Differently from machine learning approaches, often solving stance detection through black-box analyses of textual data [18], forma mentis networks produce a transparent representation ofhow individuals or populations of individuals perceive and associate knowledge about a specific topic.Through free associations [19] and sentiment patterns [20], forma mentis networks can reconstruct howknowledge is represented, structured, and perceived by people.This mental representation of a stance is grounded in years of research at the fringe of computerscience, psychology, and linguistics. Empirical and theoretical research in the cognitive sciences iden-tified these mental representations of knowledge as components of a way more complex system called mental lexicon , a repository of knowledge apt at information acquisition, processing, and use [21].The recent adoption of network science tools has shown how the large-scale, associative structure ofword knowledge in the mental lexicon is highly informative of a wide variety of cognitive processes suchas lexical processing [19, 22, 23, 24], learning and cognitive development [25, 26, 27], text structuringand writing styles [28, 29, 30, 31], creativity [32, 33], and expertise levels in specific domains [34, 5].Analogously, forma mentis networks act as approximated reconstructions on the mental constructsbuilt by individuals in their associative mental lexicon, representing their perceptions of the outerworld [16, 17].In comparison to concept maps, which have been successfully used in Education Research as toolsfor representing knowledge dependencies between parts of a syllabus or learning expertise and identi-fying key concepts for achieving learning outcomes, cfr. [35, 36, 34, 37, 38, 39, 40, 41], FMNs representa different cognitive dimension, depending on how individuals’ memory associates knowledge ratherthan just representing pre-requisites or conceptual dependencies between concepts. FMNs can there-fore represent a wider range of knowledge structures, free from any definition and mixing semantic,syntactic, visual or even phonological associations between concepts [19]. Furthermore, FMNs includealso a sentiment or affective component [20] that is absent in concept maps and which enables a closerunderstanding of emotional perception and anxiety-eliciting. Analogously to concept maps [39], formamentis networks can also identify changes in the perception or mindset of students over time [17].With such a cognitive methodology, this paper assumes an educational scope by investigatingstances toward STEM, Education, learning environments, and professionals as represented by the ag-gregated mindset of 159 Italian high schools students and of 59 international researchers (reconstructedthrough the data gathered in [16]). Differently from past approaches, this analysis focuses not on STEMsubjects but rather on educational concepts like “teacher”, “school”, “scientist”, “student”, or “learn-ing”. Most of the focus is devoted to comparisons between students’ and researchers’ perception andalso to detecting how anxiety patterns potentially arise across all the considered educational stances.The manuscript ends with a discussion of the above results in relation to the relevant literature. This section briefly reports about the data used for the current analysis. No new data were generatedfor this study. Notice that this work is based on the data provided by Stella and colleagues [16], whichincluded cues, responses, and valence labels (positive/negative/neutral). The dataset was anonymousand it did not include individual demographics of students and researchers but only overall fractionsof female/male participants and average age, which are reported in the following.
This manuscript uses the forma mentis networks released by Stella and colleagues and representativeof 159 Italian high school students and of 59 international young researchers on complex systems [16].The selected students were gathered independently on their school grades from three Italian highschools. They were all in their final year of studies, thus being representative of the Italian secondaryeducational system. No distinction in terms of socio-economic backgrounds was applied in order toguarantee a random sampling representative of the national student population. All of the interviewed2esearchers had extensive training in STEM disciplines and either possessed or were pursuing a PhDrelated to complex systems. No selection of researchers based on their backgrounds was actively per-formed. Both the populations were balanced between male and female participants (see Stella et al. [16]for more details).All participants voluntarily enrolled in the cognitive experiment leading to the construction of FMNsby providing: (i) free associations and (ii) valence scores. The first type of cognitive data was gatheredby means of a continuous free association task [19], i.e., “write up to three words coming to your mindwhen reading a given cue” (for instance, “complex”). As already reported in the Introduction, freeassociations are powerful predictors of a variety of cognitive processes, despite being independent or free from a specific definition. A selection of 50 scientific and educational concepts was used as a setof cues for the free association game. The associates were then linked to the cue, but not betweenthemselves, thus forming a network of concepts. In addition to producing free associations, participantsalso had to rate their perception of each single word on a Likert scale ranging from 1 (very negativeconcept) to 5 (very positive concept). A statistical analysis enabled Stella and colleagues to attributevalence labels “positive”, “negative”, and “neutral” to each concept, cfr. [16].Given the distinctive combination of associations and valence labels, the authors in [16] extendedthe psycholinguistic concept of word valence [20], i.e., how positively/negatively a given word is per-ceived. Stella and colleagues introduced and tested the network measure of emotional valence aura ,i.e., the tendency for a positive/negative/neutral concept to be surrounded mainly by other posi-tive/negative/neutral concepts. The authors showed how negative emotional auras are powerful iden-tifiers of anxiety-eliciting concepts, in agreement with other studies indicating a connection betweenaccumulation of negative word valence and stress prediction [20]. Positive emotional auras were notfound to indicate any specific emotional state but were rather related to positive stances toward aspecific topic. This manuscript will assess the emotional auras of educational concepts that were notdescribed or further investigated in previous approaches like [16] or [17].An example of forma mentis network is reported in Figure 1, where the concepts associated bystudents to “esperto” (expert) are reported with different font sizes. Larger words are also closer [42]to all other associated concepts in the overall forma mentis network, i.e., on average there are fewerassociations connecting a word of larger font size to all other concepts. In the reminder, in denserneighborhoods, a smaller baseline font size was used for visualization purposes, but differences in fontsizes were kept. In Figure 1, notice how “esperto” is perceived as a neutral concept (highlighted inblack) by students but also surrounded mostly by positive concepts (highlighted in cyan). This positiveaura indicates that, overall, students display a positive stance toward experts in general. This infor-mation would be lost by considering only the valence of “esperto” by itself. Notice how the networkrepresentation of linked concepts provides additional, microscopic information on the students’ stancetoward experts. For instance, the students’ mental representation of experts is strongly mediated byconcrete figures like doctors and scientists, professional figures that students can associate to appropri-ate features of knowledge-sharing, technical skills, and research expertise. These elements characterizea concrete perception, beyond general stereotypes, and an appropriate level of awareness about theroles of experts as displayed by students. materiaprofessorestudio matematica laureato laboratorio fisicafisico matematicobiologoricercatore scienziatodottore conoscenza medicinacapacitàintelligenza mestieresaperemedicoarcheologiabisognogiovane intelligenteintraprendente professionista strumento tecnico esperto
Figure 1: Example of a forma mentis network. Nodes represent concepts linked by empirical freeassociations. Conceptual links made by two or more people are thicker. Positive (negative) words arehighlighted in cyan (red). Links between positive (negative) words are highlighted with the same color.This example is based on Italian associations made by students relative to the word esperto/expert.Larger words are also closer to all other associated concepts, i.e., on average, there are fewer associationsconnecting concepts.For the sake of an easier understanding of the network visualizations, all Italian words have beentranslated by using a majority consensus rule of automated translation services (Google Translate,Bing Microsoft Translator, and DeepL). In other words, the most frequent translation was chosen foreach single Italian word as obtained from the above translation services. Translation was reported3nly at the level of labelling network visualizations. The underlying network topology was kept fixed.This might produce the repetition of different Italian words with the same English translation in thefollowing plots, but it is guaranteed to keep fixed the original structure of associations provided bystudents. Wherever the translation did not reach a consensus, the original Italian word was kept.The author, a native Italian speaker fluent in English, analyzed the quality of the translation for arandom subset of 100 Italian words and agreed with 93% of the automated translations, a percentagethat was considered good enough for mere visualization purposes.
The results of this manuscript are reported at three different stages. Firstly, the general networkstructure of forma mentis networks is analyzed and discussed as models of knowledge representation.Secondly, the emotional auras and neighborhoods of educational concepts are discussed and comparedacross students and researchers. Thirdly, more focus is devoted to understanding differences andanalogies about how students and researchers perceive and associate themselves, reporting on potentialstereotypes or distorted, anxious perceptions.
Before investigating the specific stances of students and researchers, a network analysis of FMNscan be insightful for understanding how both these groups organized and perceived their conceptualassociations and affective patterns within their STEM and educational knowledge.Table 1 reports a few key network statistics for both the students’ FMN and the experts’ FMN. De-spite the students’ FMN including almost three times as many concepts as the researchers’ FMN, boththe networks display analogous: tendency to form triangles of associations (global clustering coeffi-cient), tendency for links to connect lowly connected words to highly connected concepts (assortativitycoefficient), maximum number of associations connecting any two concepts (network diameter), andaverage number of associations linking any two words (mean network distance). For a definition ofthese measures and a brief discussion of them, please see Appendix 5 and [42].Table 1: Table of network measures for the students’ (SFMN) and the researchers’ (RFMN) formamentis networks, together with their random null models, Random S, and Random E, respectively.Null models preserve connectivity and the number of associates of a word but randomize links(i.e., they are configuration models [42]). The parentheses indicate standard errors, so that 11 (1)should be read as 11 ±
1, and are based on 50 random realizations.
Measure Students’ FMN Experts’ FMN N ull Model (Students) Null Model (Experts )Concepts 4483 1616 4483 1616Associations 11728 3185 11728 3185Clust. Coef. 0.045 0.042 0.035 (2) 0.025 (2)Assor. Coef. − − − − In a forma mentis network, every word has a number of links to other concepts, a number called alsodegree in network science [42]. The distribution of degrees for both the students’ and the researchers’FMN is heavy-tailed (see Supplementary Figure S1 and Appendix), i.e., the probability of findingwords with large degrees was not exponentially low. The heavy-tailed degree distribution, togetherwith the registered degree disassortativity [22], outlines a network structure where constellations oflowly connected words tend to link mainly to hubs. Furthermore, since words do not tend to clustertogether, there are fewer different paths connecting them and mainly going through hubs. Are hubseffective in connecting together concepts through a handful of associations? The mean distance betweenconcepts indicates that on average every two concepts are connected by 4 or 5 degrees of separation,i.e., conceptual associations. In a network with thousands of concept, such a short mean distanceindicates the crucial role played by hubs in connecting concepts with each other at distances closeto those observed in the randomized networks. These results indicate that both the forma mentisnetworks display a peculiar small-world structure , guaranteeing short distances between words likein randomized networks, but also distributing connectivity mainly through hubs rather than throughclustering, differently from the standard definition of small-world networks where high clustering isusually observed, instead (cfr. [42]).The above results indicate that hub-concepts play an important role in the structured mindsetsof both students and researchers. When describing educational concepts, the rest of the analysis willfocus mainly on hubs of relevance for educational settings. “Teacher” is a hub in the forma mentis networks of both students and researchers (see Figure 2). Stu-dents produced a considerably more clustered neighborhood for “teacher” rather than for “teaching”,4ndicative of their closer experience with teachers rather than with the act of teaching. Researchers, in-stead, associated more concepts to “teaching” rather than to “teacher”. Since most of the interviewedresearchers had also teaching experience as demonstrators, lecturers, or teaching assistants, it is onlyexpected for them to have more experience with teaching than students and hence provide a richer,more connected mental representation of such concept. For students, “teacher” by itself is a neutralconcept, mostly surrounded by neutral concepts. The presence of a non-trivial fraction of negativeand positive concepts associated with “teacher” indicates a mixed stance. In the students’ data, mostof the negative perception of “teacher” revolves around physics and mathematics, which are perceivednegatively [16], but also toward exams, grades, and quizzes, concepts that include also associations to“anxiety”. This mental structure of the students’ mindset indicates a perceived anxiety tied to thetesting and exams that are part of a teacher’s duty. However, the students’ perception is not limitedby negative concepts, but it rather includes a variety of positively-perceived words such as “beau-tiful”, “patience”, “knowledge” and “culture”. Importantly, these words indicate an understandingand appreciation of students toward the educational role of teachers, who are perceived as promotersof knowledge and culture. The researchers’ stance toward teachers is way more pragmatic, focusingmainly on the formal aspects of teaching such as “students”, “school”, and “class”. STEM expertsperceive “teaching” as a neutral concept but surround it with a positive emotional aura, identifying astrong association between “teaching” and “learning” that is missing in students. While students focuson learning outcomes in terms of grades and appreciate the orienteering figure of teachers, researchersfocus more on the places of teaching and on learning itself. Interestingly, the students’ perception of“learning” is almost completely free from the negative concepts found in the neighborhood of “teacher”,suggesting that students, like researchers, are aware of the difference between the act of teaching andthe figures performing such an act in a school setting.Figure 2:
Above:
Conceptual associations and perceptions for “teacher” (left) and “teaching” (right)in the students’ forma mentis network. Conceptual links made by two or more people are thicker.Positive (negative) words are highlighted in cyan (red). Italian words were translated in English (seeMethods).
Below:
Conceptual associations and perceptions for “teacher” (left) and “teaching” (right)in the researchers’ FMN.The differences in how students and researchers perceive teachers motivate a further look at theteachers’ educational context. “Study” is a hub in the students’ forma mentis network. Figure 3 high-lights the stances of “study” as perceived by students and researchers. STEM experts perceive “study”as a positive concept and associate it with other positive and neutral concepts. These associations aremainly pragmatic, as researchers associate “study” mainly with “university” and other STEM subjects.The students’ mindset around “study” is richer in both concrete and abstract concepts. Students per-5eive “study” as a neutral concept connected to positive words related to personal development (e.g.,future, culture, career). Even in this stance, a negative outlook on exams and their associations with“stress” both persist. Interestingly, one of these negative associations emerges from “school”.“School” is a hub in both the students’ and researchers’ forma mentis networks. Researchers per-ceive “school” as a positive concept, surrounded by a positive emotional aura (see Figure 3). Associa-tions with concepts like “fun”, “friends”, “high-school”, and “childhood” suggest that, for researchers,the school is a mental construct from the past and an important socialization avenue. The researchers’perception of “school” is devoid from any anxiety-eliciting associations, which are present in the stu-dents’ mindset, instead. The overall mindset of the 159 interviewed students identifies “school” as anegative concept, surrounded by a mostly negative emotional aura. This negative perception origi-nates mainly from quantitative disciplines such as maths and physics but also from concepts relatedto assessment like “committee”, “exams”, and “grades”. Even in the stance toward school, anxiety-related associations to “stress” and “anxiety” are present. The emerging picture is a generally anxiousperception that students have of the school setting, in particular toward well-known anxiety elicitingSTEM disciplines [1, 3, 5] and, more importantly, toward the assessment system of grading and tests,which has also been documented in other educational systems [2]. Even within this negative aura,students are able to identify the important role played by school in promoting learning and education,which are positive concepts associated with “school” itself.Figure 3:
Above:
Conceptual associations in the students’ FMN and perceptions for “school” (left)and “study” (right).
Below:
Conceptual associations in the researchers’ FMN and perceptions for“school” (left) and “study” (right). Conceptual links made by two or more people are thicker. Positive(negative) words are highlighted in cyan (red). Italian words were translated in English (see Methods).
The persistent presence of “anxiety” across the students’ perceptions of “school”, “study”, and “teacher”indicates a conceptual relationship, present in the students’ mindset, between educational settings, ac-tions, and actors and stress. A previous approach with forma mentis networks identified anxiety comingfrom a distorted perception of STEM subjects [16], but it did not focus on the mental representationof “anxiety” itself, which is reported in Figure 4. It is important to underline that “anxiety” was notamong the selected cues, but it was rather a target word associated by students. Researchers did notprovide such association when tested with the same set of cues. Confirming the relationship betweennegative valence, negative associations, and anxiety eliciting found in [20] and in [16], “anxiety” isa negative concept surrounded by a negative aura in the students’ FMN. Students provided strong6onceptual associations between “anxiety” and a set of educational concepts related to personal assess-ment, e.g., test, grade, simulation, examination, school. The strong link with “expectation” suggeststhat the test anxiety perceived by students is related to biased expectations, possibly in relation to per-formance in exams and tests. Notice that no associations are made between “anxiety” and “physics” or“maths”, so that the anxiety surrounding these STEM disciplines found in [16] should have a differentnature in comparison to the test anxiety detected here.“Fun” can be considered as antithetic to “anxiety”, and it is associated differently between the stu-dents’ and the researchers’ FMNs, whereas students associate “fun” mainly with recreational activities,and researchers provide connecting fun with making science, studying, and learning.Figure 4:
Left:
Conceptual associations and perceptions for “anxiety” and “fun” in the students’FMN.
Right:
Conceptual associations and perceptions for “fun” in the researchers’ FMN. “Anxiety”was not reported or associated by the researchers.
Beyond their perception of surrounding reality, it is interesting to investigate also how students andyoung scientists perceive themselves. These self-perceptions can be informative about the presence ofspecific stereotypes or potential biases about the main actors of STEM learning and research. Figure 5reports the FMN structure around “student” and “scientist” in both high schoolers and researchers.Students build up a mental representation of themselves that is neutral but associated with severalpositive concepts about personal growth, education and career building, as indicated by links with“happy”, “commitment”, “learning” and “career”. Free associations and affect labels identify a clusterof concepts linked to students that is about “work” and “specialization”, suggesting the students’projections about their future in the job market. Even in the positive aura of “student” as perceivedby students, there are negative outliers related to school, grades, and anxiety. “Maturity” in Italianindicates also the final exam at the end of high school, a concept perceived negatively and stronglyrelated by students to their mental construct or self-perception. In addition, researchers perceivethe idea of “student” as a neutral concept and surround it with positive words. In the researchers’FMN, however, students are represented not only as components of the educational system but alsoas active agents of the research environment (see associations with “scientific” and “conference”).Differently from students, researchers do not associate “student” to any concept specifically relatedto the job market. The researchers’ perception of “scientist” is neutral, with few associations mainlyfocused to specific types of scientists. The students’ FMN offers a much richer stance. Studentsperceive “scientist” as a positive concept surrounded by a positive emotional aura. This finding,in addition to the specific associations provided like “scientist-good” or “scientist-intelligent”, indicatean appreciation of students toward scientists in general. Through clusters of associations with researchand STEM disciplines, students display a good awareness of the role played by scientists in promotingscience across the spectrum of STEM disciplines through “research”, “theory” and “experiments”.Within this overwhelmingly positive, detailed and non-stereotypical perception of scientists, there isalso a strong cognitive association between “scientist” and “crazy”, indicating the permanence ofa small stereotype about “mad scientists”. The forma mentis network of students indicates that the“mad genius” stereotype co-exists with a positive and mostly non-stereotypical perception of scientists.The ability for the forma mentis network to capture potential stereotypes in the mental representationof specific categories of individuals opens important directions for future research.7 nxiety matter maturity teacher school studyuniversity universityvote teacher graduate time self - organization classroom teach class book studentlearning tasks educationsubjects votesstudy specialization knowledgework commitmentfatigue friendspartner desperatehappycrisis template sociality backpack student study theorygraduate branch experiment formulas laboratory science expert physicalmathematicalbiologist researcher discoveryrelativityresearchreality person competent scholar specialized einsteintest manampoulegoodintelligentprofession beakeralbhawking crazy prove _ stato scientist conferencephysicsfun schooluniversity scientificteaching teacher classexamyoungcuriouschildish student sciencetoolculturalbiologistgameexpert coat sounds physicist scientist Figure 5:
Above:
Conceptual associations and perceptions for “student” and “scientist” in the stu-dents’ FMN.
Below: neighborhoods for “student” and “scientist” and in the researchers’ FMN. Con-ceptual links made by two or more people are thicker. Positive (negative) words are highlighted incyan (red). Italian words were translated in English (see Methods).
This manuscript adopted the recent framework of forma mentis network [16] for reconstructing, quan-tifying and comparing how high school students and researchers perceive actors, places, and elementsof relevance for education. The analysis focused on concepts such as “teacher”, “study”, “learning”,“school”, “student”, and “researcher” and identified several differences in the mindsets of studentsand researchers. Consistently across all the stances focusing on such concepts, STEM experts reportedrather pragmatic views, more focused on STEM disciplines and related to learning as a positive, fun,and rewarding experience. Instead, students exhibited a more complex range of perceptions, rang-ing from the negative associations with STEM disciplines like statistics or physics or maths to thepositive identification of “study”, “teachers”, and “scientists” as promoters of personal and societaldevelopment through knowledge and education. In comparison to STEM experts, students exhibiteda stronger awareness of the relevance of education for better approaching the job market.The most crucial difference in mindsets was found within the mental representation of “school”,which is perceived and linked negatively by students and positively by researchers. Considering thatthe current investigation involves 159 students, this difference has to be pinpointed to systematicdifferences in the perception of school rather than in idiosyncratic differences attributed to personalpreferences. Considering the presence of several strong conceptual associations between “school”,“stress”, “anxiety”, and other concepts related to learning assessment (e.g., “grades”, “committee”,“exams”), forma mentis networks highlight the presence of an anxious perception of school affectingthe whole student population. Anxiety-focused conceptual associations persisted in almost every othereducational stance investigated here, indicating a strong influence of such negative emotion over theperception of education as portrayed by students. On the one hand, it might be that this anxietyis only the symptom of the final exam (”maturit” in Italian), at the end of high school, all the in-terviewed students were preparing for. On the other hand, this anxiety did not interest all STEMdisciplines or educational cues in the FMN (see also [16]) but rather focused only on specific topics,thus suggesting that the students’ anxiety did not distribute on their whole scientific mindset butrather concentrated only around specific parts of it. Such concentration is an indication that theremight be not just one general feeling of anxiety permeating all the tested mindsets but rather multiple types of anxiety affecting mental constructs in different ways. Detecting and understanding thesedifferent sources for anxiety becomes key to enabling intervention policies for reducing stress in stu-dents. In their FMN, students portrayed “anxiety” as strongly connected to performance anxiety intests, a well documented cause of stress [9, 2] that could be prevented by promoting creative inter-actions through cooperative learning of STEM subjects, as tested in chemistry teaching classes [7].Conceptual associations between “anxiety” and STEM subjects were missing in the students’ FMN,despite anxiety-eliciting being detected in the negative auras of disciplines like maths, physics, and8tatistics [16]. These missing links suggest the presence of a different type of anxiety affecting howstudents perceive these subjects, beyond assessment in itself. Importantly, several studies identifiedSTEM subjects as potential sources of distress in students [1, 3, 15, 5], often caused by an erroneousperception that these disciplines are inherently hard, require too much effort, cannot be understood byanyone and are dry, without any specific relevance for everyday life. This distorted perception is partlydue also to specific teaching styles presenting STEM subjects as separate compartments incompleteby themselves and detached from reality [8, 43]. These issues might be tackled by using innovativetools from cognitive network science, mapping students’ interactions, discussions, mindsets, and per-formance [37, 44, 34, 5, 16] and offering data-driven support to managing teaching and learning inclassroom settings [38]. In addition, the adoption of persuasive technologies [45] and a renewed focuson Jantsch’s interdisciplinarity [46, 8, 47] could help with addressing the above distorted perceptionby making students aware of the creative, fun side of the above STEM subjects in relation to thecomplexity of the real world. The current analysis indicates that such connection between “fun” and“science” characterises STEM experts while it is missing in students. As a concrete example, buildingconceptual links between history and physics and presenting students with reconstructions about thehistorical role of physics experiments of the 19th century has been indicated as a rather powerful wayof favoring physics teaching [35]. Although resistance-to-change [48] poses a challenge for innovatingteaching styles and curricula, the advent of tools reducing anxiety and favoring concentration in stu-dents is important not only for its self-evident psychological benefits but also in terms of facilitatingand enhancing students’ performance in STEM [6, 4] and students’ appreciation of STEM careers [15].The microscopic structure of students’ and researchers’ mindsets reconstructed by FMNs enabledalso a comparison between self-perceptions. Young scientists reported a schematic perception of them-selves, mainly in relation to STEM fields. They also perceived students in relation to the educationalenvironment but also as associated with scientific conferences. Students perceived themselves as mainlyneutral, with a positive attitude toward personal growth through learning, work and university edu-cation. Importantly, students perceived scientists as an overwhelmingly positive figure, surrounded bya positive emotional aura and associated with traits of goodness and intelligence and devoid of anyanxiety-eliciting conceptual association. High schoolers also associated “scientist” with “crazy”, sug-gesting some awareness of the stereotypical mental picture of the mad genius [10, 12, 11], a stereotypeoverwhelmingly present in fiction and media and which dangerously obfuscates the work of scientistsand the scientific method. The ability for students to associate “scientist” both with general-levelconcepts about knowledge and specific tools and fields of research in STEM indicates a mainly non-stereotypical perception, which is an important stepping stone for improving their perception of STEMsubjects too. Importantly, the overall non-stereotypical perception of scientists reported by studentsindicates that stereotype threat [14] did not affect the forma mentis of students and cannot, therefore,be considered a strong cause for the negative, anxious perception reported in [16]. Overall, thesefindings pose forma mentis networks as a novel alternative to other techniques quantifying scientists’perception such as picture drawing or questionnaires [10] for future research directions.Although forma mentis networks offer important information about the mental representation ofstances, the above analysis is limited under some aspects. For instance, the current analysis focuseson the population level but does not provide insights about individual students or researchers. Al-though further research in this direction is still necessary, a first attempt of using individual-levelforma mentis networks has been done by Stella and Zaytseva, who successfully used FMNs for detect-ing changes in the mindsets of a small group of students over a summer job experience [17]. Buildingindividual-level FMNs requires more cues and is therefore more time consuming when interviewinglarge groups of participants, but it can provide longitudinal characterization of stances in specific pop-ulations. Another limit of the current analysis is the lack of a temporal dimension. The currentlyanalyzed snapshots enable distinguishing crucial differences between students and experts but cannotpinpoint exactly how these differences emerged over time. Following a cohort of students over a shortamount of time, analogously to Stella and Zaytseva’s work [17], might better identify the role playedby competence acquisition over the detected students’ anxiety.
Beyond the above data-related limitations, forma mentis networks have the power to explore how dif-ferent stances co-exist together in the overall mindset of a given group. In this way, FMNs can be usedfor detecting different types of anxiety affecting the perception of STEM within student populations,without the need for hard-coding specific questions as in standard surveys. As reported in the currentanalysis, within the same framework of FMNs, evidence for STEM anxiety [1], test anxiety [2], and anon-stereotypical perception of scientists, indicating a lack of stereotype threat patterns [14], were allidentified as co-occurring within the mindset of high-school students.Overall, the simplicity of the cognitive task behind network construction, the microscopic accessto conceptual knowledge and emotions and the quantitative results reported in the above analysisindicate forma mentis networks as providers of important information for better understanding andaddressing anxiety and stereotypical perceptions in educational contexts and intervention policies.9 unding
This research received no external funding.
Acknowledgements
The author acknowledges Ruth Lazkoz for interesting discussion about the stereotypes of scientists inthe relevant literature. The author acknowledges also Sarah De Nigris, Aleksandra Aloric, and CynthiaS. Q. Siew for insightful discussion about education and network science.
Conflicts of Interest
The author is employed at Complex Science Consulting. The funders had no role in the design of thestudy; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in thedecision to publish the results.
Appendix 1: Network Measures of Forma Mentis Networks
In the main text, several network metrics for the FMNs of students and researchers are presentedand briefly discussed. This Appendix provides additional details about such metrics, focusing overthe global clustering coefficient reported in Table 1 and the degree distribution discussed in the Re-sults section.Global clustering coefficient measures how many triangles are present in the network [42] and canrange between 0 (e.g., tree network, no triangles) and 1 (e.g., complete graph, all possible trianglesare formed). The modest values of clustering detected in both of the FMNs indicate a weak tendencyfor concepts to form triangles of associations and cluster together. Randomizing conceptual associa-tions while preserving the number of links of each word (i.e., degree) produces null models with lowerclustering coefficients but of the same order of magnitude of the empirical networks. This compari-son indicates that the degree distribution partially induces but cannot fully explain word clustering.Additional cognitive phenomena, such as semantic similarity [22], might foster triangle formation andglobal clustering despite network construction (where recalled words are linked only to the cue andnot between themselves).A closer look at the degree distribution, reported in Supplementary Figure S1, indicates that boththe forma mentis networks are rich in low-degree nodes and feature heavy-tailed degree distributionswith hubs [42], i.e., a few words involved in a large fraction of associations. The tipping points in thedegree distribution are used for identifying hubs, i.e., nodes with degree higher than 30 (13) in thestudents’ (researchers’) FMN.
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