1 Factors explaining students’ attitudes towards learning in genetics and belief in genetic determinism

2

3 Tuomas Aivelo1,*, Anna Uitto2

4 1: Faculty of Biological and Environmental Sciences, University of Helsinki

5 2: Faculty of Educational Sciences, University of Helsinki

6 * Corresponding author: [email protected]

7 STUDENT ATTITUDES ON GENETICS

8 Abstract

9 It is important to know how current education affects students’ attitudes towards learning,

10 specifically in a quickly evolving and societally relevant field of biology such as genetics. The aim

11 of this study is to examine how teacher and student-related factors explain secondary school

12 students’ attitudes towards the applications of genetics and learning in genetics. In total 421

13 students aged between 17 and 20 from ten schools participated in the study. We measured students’

14 liking of, self-concept in and experienced utility of genetics and students’ attitude towards gene

15 technology and belief in genetic determinism. We carried out item response theory based modelling

16 by including teachers’ teaching emphases, learning materials, student gender and the number of

17 attended biology courses as explanatory variables. The attitude towards gene technology and belief

18 in genetic determinism correlated with all independent factors. Male students’ attitude towards gene

19 technology was more liberal; they had higher self-concept, but experienced less utility in genetics

20 and their belief in genetic determinism was weaker than in women. If the teacher’s emphasis was on

21 Heredity or if the textbook with stronger Mendelian emphasis was used in teaching, students had

22 more negative attitudes towards learning in genetics, but the belief in genetic determinism was

23 stronger. In comparison, teacher’s Developmental emphasis explained students’ lower belief in

24 genetic determinism, whereas Structural emphasis correlated with students’ liking of genetics. The

25 results suggest that teachers’ approaches in genetics teaching as well as learning materials need

26 updates to fulfil the needs for genetics literacy in current science education.

27

28 Keywords: item response theory (IRT), student attitudes, socioscientific issues, biology education,

29 upper secondary school STUDENT ATTITUDES ON GENETICS

30 Introduction

31 As a form of scientific literacy, genetics literacy has been presented as a required skill in the 21st

32 century (Boerwinkel, Yarden, & Waarlo, 2017). More and more technological advances, which

33 might shape society and human beings themselves, have been presented to a wider audience.

34 Several genetics-related issues already are or are expected to become widely relevant policy issues:

35 gene technology in food production or disease treatment, genetic tests on animals and humans, and

36 study of human ancestry through population genetic tools. Nevertheless, the teaching of genetics

37 has been slow to follow new societal importance of genetics literacy. Consequently, there has been

38 a substantial debate on the teaching of genetics, the focus of genetics teaching and the role of

39 societal issues in teaching (Chapman et al., 2019; McElhinny, Dougherty, Bowling, & Libarkin,

40 2014; Redfield, 2012; Smith & Gericke, 2013).

41 Indeed, it is important to know how current teaching approaches and learning materials influence

42 students’ attitudes towards genetics and socio-scientific issues (SSI), such as gene technology and

43 genetic determinism. We present a survey study of Finnish upper secondary school students (grades

44 10-12) on their attitudes towards studying genetics and the use of gene technology, and belief in

45 genetic determinism. Our prior studies with the same respondents have shown that their teachers

46 used differing emphases in teaching genetics (Aivelo & Uitto, 2019), so that they emphasized either

47 gene structure and function (Structural emphasis), continuity of DNA throughout evolution

48 (Hereditary emphasis), or genotype-to-phenotype link (Developmental emphasis). These emphases

49 are not only content-related, but they also pertain to how teachers perceive student interests in

50 genetics and how much they use human contexts in their teaching. We have also analyzed the

51 contents of the biology textbooks used by the same students (Aivelo & Uitto, 2015) and the results

52 indicated that while the textbooks are highly similar in contents and ordering of the contents, they

53 do contain substantial differences in which gene models are used (c.f., Gericke, 2008). STUDENT ATTITUDES ON GENETICS

54 Consequently, in this study, we have a unique setting to tease apart the relationships between

55 genetics teaching, textbooks, and student attitudes. The aim of the present study is to discover the

56 relative importance of teacher- and student-related factors on student attitudes towards learning of

57 genetics and gene technology as well as their belief in genetic determinism. Teacher-related factors

58 included their emphasis in secondary school genetics teaching and the contents of biology textbooks

59 in regard to genetics, while the student-related factors included gender and the number of biology

60 courses studied during the grades 10 to 12.

61 Attitudes towards science learning in school

62 An attitude has been defined as an immediate disposition towards concrete or abstract objects,

63 events, or people in one’s environment, with some degree of favor or disfavor (Eagly & Chaiken,

64 1993; Potvin & Hasni, 2014). In science education, general and impersonal evaluation perspectives

65 are decisive for an attitude (Krapp & Prenzel, 2011). According to Osborne, Simon, and Collins

66 (2003), attitudes towards science and science education do not consist of a single construct, but a

67 large number of subconstructs that to varying degrees shape attitudes towards science. For instance,

68 anxiety towards science, enjoyment of science, belief in the utility of science, and self-esteem vis-à-

69 vis science reflect different aspects or dimensions of students’ attitudes towards school science. In

70 science education, biology is commonly found to be a favorite subject, especially among young

71 women (Britner, 2008; Osborne et al., 2003; Uitto, 2014)

72 While genetics is commonly given as an example of a difficult topic in biology learning (Bahar,

73 Johnstone, & Hansell, 1999; Banet & Ayuso, 2000), there are not many investigations of factors

74 relating to students’ attitudes towards studying genetics and its applications. For instance,

75 Taiwanese primary and secondary school students found genetics interesting, important, and

76 relevant, but also difficult and too mathematical, though their attitudes were less polarized the older

77 they were (Chu, 2008).

78 Attitude toward gene technology STUDENT ATTITUDES ON GENETICS

79 There is a positive relationship between knowledge and attitudes towards science in general (Allum,

80 Sturgis, Tabourazi, & Brunton-Smith, 2008; Sturgis, Brunton-Smith, & Fife-Schaw, 2010).

81 Nevertheless, while an understanding of genetics is generally limited among the members of the

82 general public, they have often been found to have positive attitudes towards gene technology

83 (Henneman, Timmermans, & Van Der Wal, 2006) and the attitudes are becoming even more

84 positive (Henneman et al., 2013).

85 Among students, Gardner and Troelstrup (2015) found five context dimensions used in

86 biotechnology attitude research: personal acceptability of gene technology for public use, attitude

87 toward research in gene technology, moral and ethical implications of gene technology for public

88 use, concern regarding the regulation of risks associated with biotechnology, and trust in groups or

89 authorities to communicate about biotechnology. They constructed and tested a questionnaire based

90 on their results and found that in general, students’ attitude towards biotechnology varied from

91 neutral to negative in different context dimensions.

92 Many personal, social, and cultural backgrounds form the framework in which students’ attitudes

93 towards gene technology can develop. For instance younger students (12-year-olds versus 17-year-

94 olds) have less favorable attitudes towards biotechnology (Dawson, 2007), suggesting that either

95 formal or informal education with increasing scientific literacy or evolving attitudes during one’s

96 lifetime may lead to more favorable attitude towards biotechnology. Nevertheless, students holding

97 negative attitude towards biotechnology can belong to two different groups: those not interested in

98 biotechnology at large and not well-informed and those who have high knowledge, but deeply

99 skeptical attitude towards personal or societal use of biotechnology (Klop & Severiens, 2007)

100 Traditionally, research on gender issues in science education has concluded that male students are

101 more favorable towards science and technology, including gene technology (Črne-Hladnik, Peklaj,

102 Košmelj, Hladnik, & Javornik, 2009; Kidman, 2010), although these gender differences are not STUDENT ATTITUDES ON GENETICS

103 always found (Uitto, 2014). Cultural aspects, such as ethnicity and world view are likely to form

104 students’ attitudes towards socio-scientific issues (Sadler & Zeidler, 2004).

105 Sadler and Zeidler (2004) state that as gene technology includes moral and ethical dilemmas, such

106 issues should not be overlooked in science education, but the students should be provided with a

107 forum to study and discuss diverse dilemmas and affects awakened by gene technology, to

108 empower them to ponder and solve complicated issues on their own. However, it is not very well

109 known, what kind of views on genetics and gene technology are emphasized in school education,

110 and how the education affects students’ attitudes to learning about genetics, gene technology and

111 SSI relating to them.

112 Belief in genetic determinism

113 One of the central misconceptions repeatedly raised in genetics teaching and learning is genetic

114 determinism. While biology as a science subscribes to a level of genetic determinism as genes are

115 responsible for guiding development of individuals, in the research of science education, genetic

116 determinism refers to much stronger version of this idea. In this context, genetic determinism “is the

117 belief that genetic contributions to phenotypes are exclusively or at least much more important than

118 the contributions of other factors such as epigenetic and environmental ones, even in the case of

119 complex traits such as behaviors and personality” (Carver, Castéra, Gericke, Evangelista, & El-

120 Hani, 2017). Carver et al. (2017) also suggest that in lieu of a deterministic model, the current

121 scientific model is rather “multifactorial” or “probabilistic.”

122 While genetic determinist discourse has long been rife in public representations of genetics research

123 in the mass media (Nelkin & Lindee, 1995), it is less clear how the audience may have understood

124 it. More recently, we know from a number of studies that public knowledge of genetics is limited

125 (Allum et al., 2008; Chapman et al., 2019; Mielby, Sandøe, & Lassen, 2013), and that the public

126 displays genetic deterministic thoughts (Condit et al., 2009), but whether this is due to deterministic STUDENT ATTITUDES ON GENETICS

127 genetic representations in the media or formal education is unknown. Previous studies show that the

128 same deterministic representations are also common in school textbooks (Carvalho dos Santos et

129 al., 2012; Castéra, Bruguière, & Clément, 2008; Gericke, Hagberg, dos Santos, Joaquim, & El-

130 Hani, 2014), and in student texts (Lewis & Kattmann, 2004; Shaw, Horne, Zhang, & Boughman,

131 2008).

132 Genetic determinism is usually manifested through the belief in a one-to-one relationship from

133 genes to traits. There is a debate whether genetic determinism is simply a misunderstanding or

134 simplification of science, or more related to deeply held beliefs, religious or otherwise. For a few

135 reasons, strong genetic determinism might not be a misunderstanding. Firstly, general knowledge

136 about genetics and beliefs in genetic determinism do not correlate well (Castéra & Clément, 2014;

137 Gericke et al., 2017). Secondly, there is evidence that determinism relates to a genetic essentialist

138 belief that, echoes a plethora of intolerant attitudes, such as racism or eugenics (Dambrun,

139 Kamiejski, Haddadi, & Duarte, 2009; Shostak, Freese, Link, & Phelan, 2009). Thirdly, these

140 innatism ideas can correlate between non-tolerant attitudes (Castéra & Clément, 2014).

141 Nevertheless, it is not well known how these issues relate to students’ learning about and attitudes

142 towards genetics.

143 Genetics in Finnish upper-secondary school

144 Genetics is taught in Finland mainly as a part of biology courses. The national core curriculum

145 (Finnish National Board of Education FNBE, 2003), which was used during our study, consisted of

146 two mandatory courses for every upper-secondary school student, and three optional courses. The

147 second of the mandatory courses is Cells and Heredity, which contains molecular and cell biology

148 and basics of inheritance, and the third optional course is Biotechnology, which includes further

149 genetics, microbiology and gene technology. The Finnish national core curriculum lays out the

150 objectives of the courses and course contents on a rather general level, and it provides freedom for

151 teachers to decide on their teaching methods (Niemi, Toom, & Kallioniemi, 2012). Thus, there is a STUDENT ATTITUDES ON GENETICS

152 variation in how teachers teach genetics (Aivelo & Uitto, 2019). Interestingly, genetics is a very

153 minor part of biology teaching in lower secondary schools in Finland. Thus, we would expect that

154 upper secondary school biology teaching has a substantial effect on how students will perceive

155 genetics.

156 In general, textbooks have a very important place in teaching practices as their contents guide

157 teaching in a substantial way (DiGisi & Wilett, 1995; Nicol & Crespo, 2006). In Finnish upper-

158 secondary school, the biology textbooks are highly similar concerning genetics content (Aivelo &

159 Uitto, 2014, 2015), but they have some differences. In our previous study (Aivelo & Uitto, 2015),

160 we found that the main differences between two books were that Textbook 1 contained more

161 Biochemico-Classical gene models within genetics section, while Textbook 2 had more Mendelian

162 models. Textbook 1 also contained a specific chapter on environmental effects on phenotype, which

163 was not covered in Textbook 2. Thus, Textbook 2 presented genetics in a predominantly Mendelian

164 context, while Textbook 1 also had links inheritance to molecular genetics.

165 Study aims and objectives

166 Within science education research, there is a substantial amount of individual studies investigating

167 students’ attitudes towards learning genetics and belief in genetic determinism, but a lack of more

168 comprehensive synthesis combining different factors affecting these attitudes and beliefs. To

169 understand the relative importance of these factors, we wanted to construct a model on the

170 relationship between the dependent attitude and belief factors and independent teacher and student-

171 related factors. As for independent factors, we have studied in our previous research genetics

172 contents in biology textbooks (Aivelo & Uitto, 2015) and differences in teachers’ emphasis in

173 genetics their teaching(Aivelo & Uitto, 2019). In the present study we aimed to understand how

174 genetics content in textbooks used by the students and teachers’ emphasis in genetics teaching

175 mirror students’ attitudes towards learning genetics, gene technology and genetic determinism. We

176 used the Fennema-Sherman attitude scales as modified by Metsämuuronen (2009, 2012) to study STUDENT ATTITUDES ON GENETICS

177 students’ attitudes towards learning on genetics and modified Biohead-Citizen questionnaires

178 (Carvalho, Clément, Bogner, & Caravita, 2008) to measure students’ belief in genetic determinism.

179 We modelled students’ answers within item response theory framework (IRT; Embretson and Reise

180 2013), and in this case teacher emphasis on genetics education, type of the textbook, gender of the

181 student and number of biology courses completed by the students were used as background factors.

182 Our research questions were

183 RQ1: How strong attitudes and beliefs students hold towards genetics as a topic in learning,

184 when measured as

185 a. experienced liking of, self-concept in and utility of genetics

186 b. attitude towards gene technology and

187 c. belief in genetic determinism

188 RQ2: How are students’ attitudes towards genetics and belief in genetic determinism explained

189 by student (d,e) and teacher-level factors (f,g), namely

190 d. gender of the student

191 e. number of biology courses completed

192 f. type of biology textbook

193 g. teacher’s emphasis in genetics teaching

194 Based on previous research on gender differences in students’ attitudes towards learning of biology

195 and genetics, we expected that female students have higher liking of genetics and experience of

196 utility of genetics, while lower self-concept in genetics (Britner, 2008; Uitto, 2014) and belief in

197 genetic determinism (Keller, 2005) and less positive attitude towards the use of gene technology

198 than males (Napolitano & Ogunseitan, 1999; Sturgis et al., 2010). Also, we expected that the

199 number of biology courses correlate positively with students’ attitudes (Mielby et al., 2013), but not

200 with the belief in genetic determinism (Chapman et al., 2019). Based on our previous study on STUDENT ATTITUDES ON GENETICS

201 teacher-related factors (Aivelo & Uitto, 2019), we also expected that teachers’ emphasis in genetics

202 teaching correlate with students’ attitudes towards learning of genetics and belief in genetic

203 determinism with belief in genetic determinism has the largest differences between emphases. We

204 expect that the use of different textbooks emphasizing either inheritance within Mendelian context,

205 or the interplay of genotype and environment in forming phenotype, would correlate differently

206 with students’ beliefs in genetic determinism (Aivelo & Uitto, 2015). In general, we expected the

207 students to have low level of belief in genetic determinism and overall positive attitudes towards

208 learning of genetics and towards gene technology as found in many studies (European Food Safety

209 Authority, 2019; Henneman et al., 2013; Snell & Tarkkala, 2019).

210

211 Material and methods

212 This study is a part of a larger study on genetics teaching, also encompassing textbooks and teacher

213 perceptions of genetics teaching (Aivelo & Uitto, 2015, 2019). We distributed questionnaires with

214 the help of biology teachers whom we had interviewed previously about genetics teaching. We had

215 purposively selected 10 upper-secondary high school biology teachers from schools from Southern

216 and Western Finland to capture a variation in experience, gender, type of school and geographical

217 location in order to access variable student populations for the questionnaire (Table 1). All teachers

218 had biology as a major subject in their university master’s degree.

219 Teacher emphases in genetics teaching were a novel concept analyzed in Aivelo and Uitto (2020).

220 In brief, we can say that teachers using a Developmental emphasis see genetics from the point of

221 view of development of traits, like to use a human context, and perceive their students as being

222 interested in complex human traits and epigenetics. Teachers using a Hereditary emphasis focus on

223 the continuity of DNA through time, use humans as a context for Mendelian disorders but not for

224 complex human traits, and perceive students to be interested in gene testing and medical genetics. STUDENT ATTITUDES ON GENETICS

225 Teachers using a Structural emphasis concentrate on gene structure and function, avoid discussing a

226 human context, and perceive that students are interested in monohybrid and dihybrid crosses. These

227 emphases are based on teachers’ own descriptions of their teaching, and as such, they do not

228 describe teachers’ emphasis on any individual teaching situation, but rather what teachers see

229 genetics to constitute from a teaching perspective. These emphases are a construct of several

230 properties: central themes, use of human context in teaching and perceptions of what students are

231 most interested in, and in saturated sample, teachers surprisingly easily where classified into these

232 emphases with high agreement when asked after analysis whether they concur with the

233 classification (Aivelo & Uitto, 2019). Thus, teaching emphasis is discrete enough variable to be

234 included in this analysis as a categorical factor.

235 Questionnaire

236 We collected questionnaire data from the students during the school year 2015-2016 (Table 1). We

237 asked teachers to present the questionnaire to the students during the school day throughout the

238 school year when they had mandatory Cells and heredity and optional Biotechnology courses (see

239 FNBE, 2003) after most of the course has been completed.

240 To study the connections between the attitudes and beliefs relating to genetics learning, two

241 different survey questionnaires were combined. Firstly, we used a shortened version of Fennema

242 Sherman Mathematics Attitude Scale (FSMAS) (Fennema & Sherman 1976) to investigate

243 students’ attitudes towards learning about genetics. The scale has been used in many large-scale

244 assessments in mathematics and science education, such as TIMMS and PISA (c.f. Metsämuuronen

245 2012) measuring students’ knowledge, skills and attitudes towards learning different school

246 subjects. The shortened version is composed of three different dimensions, Liking, Self–concept and

247 Experienced utility in a specific school subject, respectively. These three dimensions, each

248 consisting of five items, which are strongly modified versions of the original scale, are also used in

249 the large-scale Finnish national achievement test in lower-secondary schools by the Finnish Board STUDENT ATTITUDES ON GENETICS

250 of Education (Metsämuuronen, 2009; Metsämuuronen & Tuohilampi, 2014). Secondly, we used the

251 Biohead-Citizen questionnaire (Carvalho et al., 2008; Castéra & Clément, 2014; Clément, Laurent,

252 & Carvalho, 2007) to measure students’ attitudes towards gene technology and belief in genetic

253 determinism. The questionnaire was built on five items per each five factors with five-point Likert-

254 scale items ranging from “I strongly disagree” to “I strongly agree” on the gene structure and

255 function, including interpretation of knowledge on genes on personal and societal levels, genetic

256 determinism, experiencing utility in genetics, self-concept in genetics, and liking genetics. The

257 questionnaire included background information on students, including their gender, age, the number

258 of attended biology courses, the textbooks they have used, and a few short open-ended questions

259 that were not analyzed for this study. The questionnaire was piloted with a group of 25 students and

260 the factors were deemed to perform satisfactorily. As the students’ age correlated strongly with the

261 number of biology courses (r = 0.71), we chose to use only the number of attended biology courses

262 instead of including ‘age’ as a variable to avoid potential issues related to collinearity.

263 Statistical analysis

264 To test our preliminary assumptions on the connections of background variables on teachers and

265 students, students’ attitudes towards learning about genetics, their attitudes towards gene

266 technology and belief in genetic determinism, the collected data was modelled using

267 multidimensional item response (latent trait) theory framework. This allows us to understand the

268 student- and teacher-level factors explaining variation in the factors outlined by our questionnaire’s

269 Likert-scale items. IRT considers each item individually; thus, it allows for items on the same scale

270 to have different response curves to latent traits (Bortolotti, Tezza, de Andrade, Bornia, & de Sousa

271 Júnior, 2013). Due to its versatility, IRT has been used previously to assess school and university

272 students’ attitudes in STEM and life science subjects (e.g., Sjaastad, 2013, Großschedl et al., 2014,

273 Romine et al., 2014, Connell et al., 2016, Guzey et al., 2016). IRT is a model-based approach in that

274 an answer to an item is seen as a function of both person and item parameters; thus, it allows for STUDENT ATTITUDES ON GENETICS

275 expanding modelling of latent traits to include explanatory factors (Lord, 1980). Person parameters

276 are assumed to be random (i.e., latent) and continuously distributed, whereas item properties are

277 fixed and inherent to items only (Chalmers, 2015). Therefore, as the results are not then dependent

278 on the set of items, but rather the particular items we used, we can use the best suited items from

279 each scale (Hambleton, 1993).

280 Our strategy contains three phases: an exploratory item analysis to examine the data structure and

281 its suitability for our purposes, confirmatory analysis to test the factor structure of the preliminary

282 model, and the explanatory analysis to model latent traits. While it is suboptimal to use the same

283 dataset for both exploratory and confirmatory analysis (Reckase, 2009), it should not be a problem

284 with this study, as the factors were already determined at the beginning of the study. Thus, the first

285 two phases are largely quality control and not theory-forming phases.

286 We explored the usability of our items with exploratory item analysis (Gorsuch, 1997). We set the

287 expected number of factors to five and allowed all items to load freely to any of these five factors.

288 Then we compared the resulting factor loadings to the expected pattern of factor loadings. We knew

289 that here Fennema-Sherman factors correlate with each other, while we had no expectations on the

290 correlations between the other two factors or their correlation to F-S factors; hence, we used

291 oblimin rotation to allow free correlation among the factors. We modelled items with a generalized

292 partial credit model (GPCM; Muraki 1992) and used estimation with Metropolis-Hastings Robbins-

293 Monro (MH-RM) algorithm (Cai, 2010b, 2010a). MH-RM is a so called hybrid approach to

294 estimating model parameters: it combines the flexibility of a Bayesian approach to computationally

295 lighter maximum likelihood estimation (Cai, 2010a). GPCM is a more constrained version of the

296 graded model as graded spacing is equal across item blocks and only adjusted by a single 'difficulty'

297 parameter. The latent variance in the model is freely estimated. The resulting model converged (i.e.,

298 reached a convergence threshold of 0.001 relatively quickly (with fewer than 300 iterations). After STUDENT ATTITUDES ON GENETICS

299 the observation of modelled factor loadings, we dropped items that performed poorly (i.e., those

300 that had evidence of multidimensionality, or a lack of loading in any factors).

301 We further validated our items and answers by implementing confirmatory item analysis along the

302 same properties as the exploratory analysis. To test the underlying assumption of local

303 independence, we computed Q3 statistics (Yen, 1984). We assessed the overall fit of the factor

304 constructs by computing M2 model fit statistics (Maydeu-Olivares & Joe, 2006). Individual item fit

305 was assessed with generalized S-X2 item fit (Kang & Chen, 2008; Orlando & Thissen, 2000) with

306 p-values adjusted for multiple comparisons with the Benjamini & Hochberg (2007) method. Person-

307 fit was assessed through Zh statistics (Drasgow, Levine, & Williams, 1984) and samples showing

308 substantial divergence (< -2.0) from expected pattern (i.e., respondents whose answers were not

309 coherent) were removed. Factor reliability was estimated with empirical reliability (Chalmers,

310 2012).

311 After validating items, factors, and answers, we built mixed effects item response theory models in

312 a generalized linear mixed modeling framework with person level covariates and random effects

313 (Chalmers, 2015). This model also used MH-RM estimation. Numerical covariates (number of

314 biology courses) were scaled to provide stability in the analysis. The model included respondent-

315 level factors gender and total number of biology courses, and teacher-related factors textbook (1

316 and 2) and teacher emphasis in genetics teaching as fixed effects, while school was added as

317 random factor. Model was validated by convergence during model iterations. We ensured that there

318 were no violations of assumptions of conditional normality and homoscedasticity by observing the

319 residual patterns. Correlations between factors are counted from the residual random variance, thus

320 considering the possible effects of the previously mentioned factors.

321 Explanatory IRT corresponds with categorical indicators structural equation modelling (SEM)

322 approach and was here preferred due to continuity by using same framework for all three parts of

323 the analysis. Furthermore, there is no partial credit models in SEM framework, though factor STUDENT ATTITUDES ON GENETICS

324 mixture models can be used to accomplish similar goals. The raw data is provided in Figshare

325 (doi:10.6084/m9.figshare.12356336.v1) and code is shared in GitHub

326 (https://github.com/aivelo/genesurvey). All phases of the analysis were run on R (R Core Team

327 2013) with the package ‘mirt’ (Chalmers, 2012).

328 Ethical viewpoints

329 Permission to conduct the study was requested from the municipalities, which are in charge of

330 education in Finland; each school principal and every participating teacher was also invited

331 separately. The questionnaires distributed to students contained information about the study and the

332 students participated voluntarily. All participating schools, teachers, and students are anonymized in

333 the research data.

334

335 Results

336 General characteristics of the data

337 We had a total of 421 respondents from 10 different schools, with a range of 19 to 65 responses per

338 school (Table 1). The response rate was higher than 90% for each group. Most of the respondents

339 were females (62.9% females, 33.0 % males, 4.1% did not answer or chose ‘other’ option). The

340 mean age of the respondents was 17.8 (± 1.9) years, and the mean total number of biology courses

341 was 3.5 (± 1.8).

342 Most of the respondents used the Textbook 1 book series (77.7%), while a minority used Textbook

343 2 (22.3%). Respondents were quite uniformly distributed from each of the teachers’ emphasis on

344 genetics contents (Developmental: 37.8%, Structural: 25.4% and Hereditary: 36.8%).

345 Exploratory, confirmatory, and explanatory analysis STUDENT ATTITUDES ON GENETICS

346 In exploratory IRT modelling, we recovered our initial expected factors, though some items

347 performed unexpectedly (Table S1). We removed items 17, 20, and 24, as they did not load in a

348 meaningful way in any of the factors, and items 6, 14, and 23 as there was substantial

349 multidimensionality in loading to various factors. All the factors had at least three well-performing

350 items in them (Figure 1).

351 We then fit a confirmatory model, which showed a good fit (RMSEA = 0.051 (0.040-0.062), TLI =

352 0.957, CFI = 0.968). Factor reliability was lower for belief in genetic determinism (0.50) and

353 attitude towards gene technology (0.47) than for liking of genetics (0.89), experiencing utility in

354 genetics (0.78) and self-concept in genetics (0.79). Items loaded on preplanned factors and while

355 their communality scores were rather low for some of the items, their fits were adequate (Table S2).

356 For Q3 statistic, only seven pairs of items had a value higher than 0.2; thus, the data suggested low

357 local dependency. Seventeen respondents had a Zh value lower than -2.0 suggesting that these

358 respondents did not fit the model; consequently, they were removed from downstream analysis.

359 Lastly, the explanatory mixed effect multilevel and multidimensional item response theory model

360 converged after 854 iterations, when it reached a standard error tolerance criteria of under 0.001.

361 Variation among schools was significant, but comparably low as random effect covariance was only

362 0.12 (95% CI: 0.02-0.22). The details of the model outputs are presented in the following chapters.

363

364 Student-level factors: gender and number of courses in biology

365 Female and male students had significantly different responses along four of the five attitude

366 factors: liking genetics was the only factor without gender difference (Figure 2). When compared to

367 women, men had a more liberal attitude towards gene technology and their belief in genetic

368 determinism was weaker, respectively. Furthermore, men experienced less utility in genetics and

369 they were more self-efficient in genetics on average than women. STUDENT ATTITUDES ON GENETICS

370 The other person-level factor in the model was the number of attended biology courses: those

371 students that had attended more biology courses so far, had significantly more liberal attitudes

372 towards gene technology, but also a stronger belief in genetic determinism; they experienced more

373 utility in genetics, they were more self-efficient and they liked genetics more (Figure 2).

374 Teacher-level factors: Teacher’s emphasis in genetics teaching and textbook

375 We included two teacher-level factors in the models: used textbook and teacher’s emphasis on

376 genetic teaching, which we had analyzed in our previous study (Aivelo & Uitto, 2019). This

377 revealed strong differences in students’ attitudes among the schools using different textbooks: the

378 students in the schools using Textbook 2 had less liberal attitudes towards gene technology, a much

379 stronger belief in genetic determinism, they experienced less utility in genetics and they were

380 slightly less self-efficient (Figure 2).

381 Teacher’s emphasis on genetics education also affected the students’ attitudes (Figure 2): teachers

382 with Hereditary emphasis had students who exhibited less liberal attitudes towards gene technology

383 and much stronger belief in genetic determinism in comparison to Structural or Developmental

384 emphasis. Furthermore, the students taught by the teachers with a Hereditary emphasis had a lesser

385 self-concept and less liking of genetics. Teachers with a Structural emphasis had students who

386 exhibited a bit stronger genetic determinism than teachers with Developmental emphasis, while

387 their students had the highest level of liking of genetics. Notably, students’ perception of the utility

388 of genetics did not differ among teachers’ emphases.

389 Correlations among attitude factors

390 All correlations among the five factors were substantially different from zero and positive, though

391 the strength of the correlation varied substantially (Table 2). The largest correlations were among

392 Fennema-Sherman factors (0.55-0.77), whereas the smallest correlations were with liberal attitude

393 towards gene technology, self-concept in genetics (0.12), and belief in genetic determinism (0.17). STUDENT ATTITUDES ON GENETICS

394 The more students liked genetics, the more liberal they were towards gene technology (0.31), and

395 they also had a stronger belief in genetic determinism (0.44). A liberal attitude towards gene

396 technology also correlated with experiencing utility in learning genetics (0.38). Students also had a

397 stronger belief in genetic determinism if they experienced utility in learning genetics (0.26), or were

398 self-efficient in genetics (0.24).

399

400 Discussion

401 We present here modelling work based on the previous analysis of textbook contents and teacher

402 interviews with additional student questionnaires, thus bringing together commonly separately

403 studied aspects of science education. Our model explained the impact of both teacher- and student-

404 related factors on secondary school students’ attitudes towards learning genetics and gene

405 technology and their belief in genetic determinism. In student-related factors, gender differences

406 were found in most of the attitudes, whereas the number of attended biology courses significantly

407 explained differences in all attitude and belief dimensions. Differences in students’ attitudes were

408 also substantially explained by teacher’s emphasis in genetics teaching as well as the content

409 emphasis of the biology textbooks.

410 Our study suggests that in general, Finnish secondary school students liked to study genetics; they

411 had mostly favorable attitude towards gene technology and they did not hold strong belief in genetic

412 determinism. These findings are in line with the present studies that in general, overall civic

413 attitudes towards gene technology are favorable in many European countries (EFSA, 2019;

414 Henneman et al., 2013; Snell & Tarkkala, 2019).

415 In our study biology teachers’ educational choices, meaning used textbook or teaching emphasis,

416 seemed to be crucial in shaping their teaching and consequently had an surprisingly substantial

417 impact on their students’ attitudes. In our model, these factors explained variation in students’ STUDENT ATTITUDES ON GENETICS

418 attitudes towards the learning: liking genetics, self-concept in genetics and with their conceptions

419 on the utility of genetics. This can be expected as in general, teachers’ perceptions of their subject

420 and choice of learning materials is known to influence students’ attitudes, self-beliefs, learning and

421 achievements (Osborne et al., 2003).

422 Student-related factors

423 We found that students’ orientation and increasing knowledge of genetics, here roughly estimated

424 as the number of attended biology courses, has a low, but consistent correlation with students’

425 attitudes and beliefs. The number of attended biology courses explained more favorable attitudes

426 towards learning about genetics, but unexpectedly also students’ stronger belief in genetic

427 determinism.

428 The connection between studying more biology and having stronger belief in genetic determinism is

429 astonishing as that strong belief in genetic determinism contradicts current scientific understanding

430 of multifactorial gene function (Carver et al., 2017). The result contrasts to Chapman et al. (2019)

431 who found a negative correlation between genetic knowledge and genetic deterministic ideas.

432 Notably, Gericke et al. (2017) did not find any relationship between genetic knowledge and genetic

433 determinism among Brazilian university students, and Castéra and Clément (2014) did not find any

434 difference between innatist ideas between European and Mediterranean biology teachers and non-

435 biology teachers. Nevertheless, in our study these were low effects (corresponding to 0.08-0.15

436 points on the scale per course), but as there are five mandatory and optional biology courses

437 concerning genetics at least in some degree, and some schools have a substantially higher number

438 of optional biology courses, this might add up to substantial effects on beliefs during upper-

439 secondary education.

440 There might be several reasons for the result: for example, both studied textbooks have been shown

441 to exhibit a number of genetic determinist traits (Aivelo & Uitto, 2015); indeed, deterministic views STUDENT ATTITUDES ON GENETICS

442 are common in school textbooks (Castera et al., 2008; Carvalho dos Santos et al., 2012, Gericke et

443 al., 2014). Thus, by studying with such textbooks with emphasis on Mendelian genetics, the

444 students might pick up stronger genetic determinism (although this might have not been the original

445 intent of the textbook writers). Obviously, the causality can also be reversed: those students who

446 think more strongly about genetic determinism are more likely to study genetics, as they feel it as

447 more important to understand. Indeed, there was a positive correlation between belief in genetic

448 determinism and experiencing utility in learning genetics.

449 As expected, the students who had taken more courses in biology, also liked genetics more, had

450 higher self-concept and experienced a stronger utility for knowing genetics. The students who did

451 more courses in biology had obviously their specific interest and motivations to learn more about

452 biology and genetics. The strongest relationship between the number of attended courses was with

453 the positive attitude to gene technology. This suggests that the students who study the most biology

454 also either become or already are more positive towards gene technology.

455 As found in many studies (Mielby et al., 2013; Olofsson, Öhman, & Rashid, 2006; Sturgis et al.,

456 2010), gender differences were clear in some factors: male students had substantially more positive

457 attitude towards gene technology, and also, as previously shown in different science subjects

458 (Britner, 2008; Uitto, 2014), male students in our study also had higher self-concept in genetics.

459 Notably, in a Finnish study, Uitto (2014) did not find any gender difference in attitudes to

460 secondary school biology, but in general academic self-efficacy, in mathematics and other science

461 subjects the self-efficacy of male students exceeded that of females. Notably, in our study male

462 respondents had weaker belief in genetic determinism, whereas in previous study Gericke et al.

463 (2017) did not find gender differences at all. As with the number of biology courses, also in gender

464 there was an evident link between belief in genetic determinism and experiencing utility in genetics.

465 Teacher-related factors STUDENT ATTITUDES ON GENETICS

466 We found that biology textbooks and teacher emphases, defined as Structural, Hereditary and

467 Developmental (Aivelo and Uitto, 2019) correlated more strongly than expected with student

468 attitudes towards learning about genetics. Most notably students whose teacher used a Hereditary

469 approach had much stronger belief in genetic determinism than students whose teachers used a

470 Developmental or Structural approach in their teaching. Furthermore, the Hereditary approach

471 correlated strongly with students’ negative attitude towards gene technology. A Structural approach

472 in turn correlated with higher liking in genetics, while Hereditary was linked to lower, when the

473 results are compared to the Developmental approach of the teacher.

474 These results were unexpected in a sense that in our previous analysis Hereditary emphasis was

475 seen to be a conceptual middle ground between a human-contextualized Developmental approach

476 that focuses on the genotype to phenotype link, and the Structural approach that focuses on gene

477 structure and function, but in which human-context was avoided (Aivelo & Uitto, 2019).

478 Nevertheless, there were also other differences among the emphases, such as teachers’ perception of

479 student interest in different topics in genetics. For example, teachers using a Structural emphasis

480 think their students are interested in basic genetic knowledge, such as monohybrid and dihybrid

481 courses, while teachers who used a Hereditary emphasis thought that applications of genetic

482 knowledge, such as gene tests and medical genetics, were interesting, and teachers that used a

483 Developmental emphasis, thought students to prefer studying human genetics, epigenetics and the

484 inheritance of complex traits.

485 Textbooks are a dominant resource for the science classroom, and, in general, the textbook chosen

486 by the teacher contributes to students’ genetic and scientific literacy in many ways (Calado,

487 Scharfenberg, & Bogner, 2015; Osborne et al., 2003). In our study, the difference between the

488 students using either of the textbooks was substantial in many ways. Most notably, in our model the

489 use of Textbook 2 explained students’ stronger belief in genetic determinism. Furthermore, the

490 learners using Textbook 2 had a lower self-concept and they experienced less utility in genetics; STUDENT ATTITUDES ON GENETICS

491 they also had a less liberal attitude towards gene technology. Textbook 2 emphasized Mendelian

492 genetics and less the environmental effects on phenotype formation, suggesting a link between

493 stronger genetic determinism and lack of discussion of environmental effects in genotype to

494 phenotype link (Aivelo & Uitto, 2015). A link between the emphasis on teaching Mendelian

495 genetics and genetic determinism has been suggested in numerous studies (Donovan, 2014;

496 Jamieson & Radick, 2017; Keller, 2005).

497 Correlations among the attitude factors

498 In this study, three previously formulated factors from modified Fennema-Sherman correlated

499 strongly with each other (0.55-0.77), while the belief in genetic determinism and positive attitude to

500 gene technology were more divergent. Unsurprisingly, experiencing utility in gene technology

501 correlated most strongly with positive attitudes: if the students thought that genetics is useful, they

502 were also more open to the application of gene technology. This is a general observation for the

503 perceived value of genetic technology in many different contexts (Hossain, Onyango, Schilling,

504 Hallman, & Adelaja, 2003; Kopits, Chen, Roberts, Uhlmann, & Green, 2011; Saba & Vassallo,

505 2002). Self-concept and different attitude dimensions had rather low correlation, suggesting that

506 students’ self-concept in genetics performance is not necessarily linked to more positive attitude

507 towards gene technology. This suggests that there is only a weak link on how much students

508 perceive to understand biology and how positively they approach applications of biology. In

509 general, this is in line with other studies that show a small effect between knowledge and positive

510 attitudes toward applications (Chu, 2008; Knight & Smith, 2010; Maes, Bourgonjon, Gheysen, &

511 Valcke, 2018; Šorgo & Ambrožič-Dolinšek, 2010).

512 Limitations of the study STUDENT ATTITUDES ON GENETICS

513 Due to aiming to collect a large sample size, we opted for a short questionnaire, i.e., a limited

514 number of items per factor. While this might cause suboptimality in the modelling of the factors, the

515 items seemed to perform adequately, and the model was successfully parametrized.

516 We measured the belief in genetic determinism with only three items. There was a distinction

517 between items as the students described quite high agreement with two items on medical genetics,

518 while having low agreement with the item on human intelligence. This seems to be in line with the

519 findings of Gericke et al. (2017), suggesting that the belief in genetic determinism consists of two

520 dimensions: social behavior and biological traits, and our findings seem to be compatible with

521 theirs. These results also align with interview studies (Andreychik & Gill, 2015; Condit et al.,

522 2009). The correlation between the number of attended courses and genetic determinism can also be

523 affected by the problem of construct validity: the students who have studied more genetics may

524 understand the items of the questionnaire in a different way than the beginners. Nevertheless, our

525 approach minimizes this problem as each item is modelled as an individual item with different

526 response curves. Similarly, attitude towards gene technology are a multi-component construct and

527 our items are similar to factor called by Klop & Severiens, (2007) as “basic emotions on

528 biotechnology”. Thus, they measure only one aspect of the attitude towards biotechnology.

529 It should be noted, though, while there is no expectation that teachers with different emphases are

530 non-randomly distributed in schools, the textbook selection is most likely not random. Teachers

531 usually choose textbook series, which they like, and find more suitable for their students. This

532 means that book choice could also correlate with teacher’s beliefs on students’ knowledge: in

533 interviews, teachers have mentioned that they might feel that Textbook 1 is “too demanding” for

534 their students. Furthermore, as teacher emphases are based on what teachers perceive as the most

535 important contents and contexts in genetics teaching, their emphasis probably affected the textbook

536 choice. STUDENT ATTITUDES ON GENETICS

537 We do not know what kind of teaching emphases the earlier biology teachers or classroom teachers

538 in primary and lower secondary school have used, and the role of prior content knowledge about

539 genetics might play a substantial role. Nevertheless, genetics plays a very minor role in primary and

540 lower secondary school and is mentioned usually only in passing. Thus, we would expect that

541 genetics would be one of the fields of biology where the impact of the biology teachers would be

542 most substantial in Finnish upper secondary school. This study also further validates the existence

543 of these approaches as there are clear differences between teachers using different teaching

544 approaches.

545 Implications on teaching practices

546 Though we compared only two textbooks, they are used by almost all upper secondary school

547 students in Finland. The differences were stark; thus, they highlighted the importance of teachers

548 making informed choices when they select textbooks. While not much studied, textbook contents

549 have been shown to significantly influence student interest (Kloser, 2013). In Finland, the selection

550 of textbooks is generally up to each individual teacher, thus they have a substantial responsibility

551 for choosing suitable textbooks. The clear differences between the textbooks echo the results

552 obtained from mathematics textbooks, where the use of books from the same series leads to

553 cumulative effects in student learning (van den Ham & Heinze, 2018). As outlined by Johansson

554 (2006), textbooks not only make learning possible, but also function as an obstacle to learning;

555 therefore, they should be carefully considered.

556 Importantly, our model suggests that teachers’ practices can shape students’ attitudes towards

557 learning genetics. Thus, the teachers should be more aware of how their choices to teach genetics

558 are able to shape students’ perceptions and attitudes. Although not intended, teaching can enhance

559 belief in genetic determinism. It is well-known that genetic determinism is a persuasive

560 misconception that can arise from problems in combining classical and molecular genetics models

561 (Gericke & Smith, 2014). STUDENT ATTITUDES ON GENETICS

562 While we need more research on how actual classroom and teaching practices shape student

563 attitudes, we believe that our results already suggest that the approach we have named as

564 Developmental, which uses human context in teaching genetics, including complex human traits,

565 and takes genotype-to-phenotype link to center stage, leads to lower genetic determinism than

566 others and does not compare negatively to other emphases in student attitudes. This link is not

567 surprising as it might make sense to counter genetic deterministic ideas in their own context. For

568 example, learning about human genetic variation counters students’ racial bias (Donovan, 2019).

569 Our study showed that the students who studied more genetics also had more favorable attitude

570 towards gene technology. This link suggests that using more SSI in teaching could be broadly

571 helpful in countering deterministic or uncritical approaches to genetics and gene technology, and in

572 broadening an understanding and implications of genetics in society. While teachers generally

573 emphasize the importance of content knowledge in understanding SSI (Tidemand & Nielsen, 2017),

574 these concepts should be incorporated in the teaching from the very beginning of genetics education

575 (Sadler & Zeidler, 2005). Furthermore, incorporating SSI in teaching can also enhance students’

576 interest and motivation in learning biology (Kidman, 2010; Logan & Skamp, 2013; Sadler &

577 Dawson, 2012).

578

579 Conclusion

580 Our study indicates that both the students’ personal factors, such as gender and interest in studying

581 biology in upper-secondary school as well as teacher-related factors, such as teachers’ emphases in

582 genetics teaching and their choice of textbook, explain students’ attitudes and beliefs when learning

583 genetics. Unexpectedly, students who had studied more biology, were not only more interested in

584 genetics and more positive about the benefits of gene technology, but also held stronger belief in

585 genetic determinism. Our study shows the benefits of simultaneously analyzing textbook contents, STUDENT ATTITUDES ON GENETICS

586 teacher interviews and student questionnaires to provide a comprehensive picture on genetics

587 learning. Practical implications include that teachers should discuss more broadly the societal

588 implications of genetic knowledge and foster critical approaches to obsolescent interpretations of

589 genetics contents and gene technology provided by textbooks (Aivelo & Uitto, 2015). Although on

590 average students did not hold very strong deterministic belief, students’ beliefs became stronger as

591 they studied more courses in biology. In addition, students with a more positive attitude towards

592 learning genetics might see gene-related socio-scientific issues, such as the heredity of human

593 intelligence, to depend only on genes. We suggest that teachers’ approaches in genetics teaching as

594 well as their choice of learning materials need updates to enhance students’ genetics literacy in

595 upper-secondary school science education.

596

597 Disclosure statement

598 Tuomas Aivelo has participated in writing biology textbooks for upper-secondary school biology

599 for eOppi Oy. None of the teachers involved in this study used biology textbooks from eOppi Oy.

600

601 Acknowledgments

602 The authors wish to thank ten biology teachers and their students who participated in this study, two

603 anonymous reviewers on constructive comments and Marlene Boemer for checking the language in

604 manuscript.

605 STUDENT ATTITUDES ON GENETICS

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775 Knight, J. K., & Smith, M. K. (2010). Different but equal? How nonmajors and majors approach 776 and learn genetics. CBE-Life Sciences Education, 9, 34–44. https://doi.org/10.1187/cbe.09-07- 777 0047 778 Kopits, I. M., Chen, C., Roberts, J. S., Uhlmann, W., & Green, R. C. (2011). Willingness to pay for 779 genetic testing for Alzheimer’s disease: A measure of personal utility. Genetic Testing and 780 Molecular Biomarkers, 15(12), 871–875. https://doi.org/10.1089/gtmb.2011.0028 781 Krapp, A., & Prenzel, M. (2011). Research on interest in science: Theories, methods, and findings. 782 International Journal of Science Education, 33(1), 27–50. 783 https://doi.org/10.1080/09500693.2010.518645 784 Lewis, J., & Kattmann, U. (2004). Traits, genes, particles and information: Revisiting students’ 785 understanding of genetics. International Journal of Science Education, 26, 195–206. 786 Logan, M. R., & Skamp, K. R. (2013). The Impact of Teachers and Their Science Teaching on 787 Students’ “Science Interest”: A four-year study. International Journal of Science Education, 788 35(17), 2879–2904. https://doi.org/10.1080/09500693.2012.667167 789 Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale, 790 NJ, USA: Lawrence Erlbaum Associates. 791 Maes, J., Bourgonjon, J., Gheysen, G., & Valcke, M. (2018). Variables Affecting Secondary School 792 Students’ Willingness to Eat Genetically Modified Food Crops. Research in Science 793 Education, 48(3), 597–618. https://doi.org/10.1007/s11165-016-9580-4 794 Maydeu-Olivares, A., & Joe, H. (2006). Limited information goodness-of-fit testing in 795 multidimensional contingency tables. Psychometrika, 71(4), 713–732. 796 https://doi.org/10.1007/s11336-005-1295-9 797 McElhinny, T. L., Dougherty, M. J., Bowling, B. V., & Libarkin, J. C. (2014). The status of 798 genetics curriculum in higher education in the United States: Goals and assessment. Science 799 and Education, 23(2), 445–464. https://doi.org/10.1007/s11191-012-9566-1 800 Metsämuuronen, J. (2009). Methods Assisting Assessment; Methodological Solutions for the 801 National Assessments and Follow-Ups in the Finnish National Board of Education. 802 Oppimistulosten arviointi 1/2009. [In Finnish.]. Helsinki, Finland: Opetushallitus. 803 Metsämuuronen, J. (2012). Challenges of the Fennema-Sherman Test in the International 804 Comparisons. International Journal of Psychological Studies, 4(3), 1–22. 805 https://doi.org/10.5539/ijps.v4n3p1 806 Metsämuuronen, J., & Tuohilampi, L. (2014). Changes in Achievement in and Attitude toward 807 Mathematics of the Finnish Children from Grade 0 to 9—A Longitudinal Study. Journal of 808 Educational and Developmental Psychology, 4(2), 145–169. 809 https://doi.org/10.5539/jedp.v4n2p145 810 Mielby, H., Sandøe, P., & Lassen, J. (2013). The role of scientific knowledge in shaping public 811 attitudes to GM technologies. Public Understanding of Science, 22(2), 155–168. 812 https://doi.org/10.1177/0963662511430577 813 Muraki, E. (1992). A Generalized Partial Credit Model: Application of an EM algorithm. Applied 814 Psychological Measurement, 16(2), 159–176. https://doi.org/10.1177/014662169201600206 815 Napolitano, C. L., & Ogunseitan, O. A. (1999). Gender differences in the perception of genetic 816 engineering applied to human reproduction. Social Indicators Research, 46(2), 191–204. STUDENT ATTITUDES ON GENETICS

817 https://doi.org/10.1023/A:1006845025370 818 Nelkin, D., & Lindee, S. (1995). The DNA Mystique: The gene as a cultural icon. Oxford, UK: 819 Freeman. 820 Nicol, C. C., & Crespo, S. M. (2006). Learning to teach with mathematics textbooks: How 821 preservice teachers interpret and use curriculum materials. Educational Studies in 822 Mathematics, 62(3), 331–355. https://doi.org/10.1007/s10649-006-5423-y 823 Niemi, H., Toom, A., & Kallioniemi, A. (2012). Miracle of Education. The Principles and 824 Practices of Teaching and Learning in Finnish Schools. Rotterdam, Netherlands: Sense 825 Publishers. 826 Olofsson, A., Öhman, S., & Rashid, S. (2006). Attitudes to gene technology: The significance of 827 trust in institutions. European Societies, 8(4), 601–624. 828 https://doi.org/10.1080/14616690601002707 829 Orlando, M., & Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item 830 response theory models. Applied Psychological Measurement, 24(1), 50–64. 831 https://doi.org/10.1177/01466216000241003 832 Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature 833 and its implications. International Journal of Science Education, 25(9), 1049–1079. 834 https://doi.org/10.1080/0950069032000032199 835 Potvin, P., & Hasni, A. (2014). Interest, motivation and attitude towards science and technology at 836 K-12 levels: a systematic review of 12 years of educational research. Studies in Science 837 Education, 50(1), 85–129. https://doi.org/10.1080/03057267.2014.881626 838 Reckase, M. (2009). Multidimensional Item Response Theory. New York, USA: Springer. 839 Redfield, R. J. (2012). “Why Do We Have to Learn This Stuff?” — A New Genetics for 21st 840 Century Students. PLoS Biology, 10(7), e1001356. 841 https://doi.org/10.1371/journal.pbio.1001356 842 Romine, W., Sadler, T. D., Presley, M., & Klosterman, M. L. (2014). Student Interest in 843 Technology and Science (SITS) Survey: Development, validation, and use of a new 844 instrument. International Journal of Science and Mathematics Education, 12(2), 261–283. 845 https://doi.org/10.1007/s10763-013-9410-3 846 Saba, A., & Vassallo, M. (2002). Consumer attitudes toward the use of gene technology in tomato 847 production. Food Quality and Preference, 13(1), 13–21. https://doi.org/10.1016/S0950- 848 3293(01)00052-0 849 Sadler, T. D., & Dawson, V. (2012). Socio-scientific Issues in Science Education: Contexts for the 850 Promotion of Key Learning Outcomes BT - Second International Handbook of Science 851 Education. In B. J. Fraser, K. Tobin, & C. J. McRobbie (Eds.) (pp. 799–809). Dordrecht: 852 Springer Netherlands. https://doi.org/10.1007/978-1-4020-9041-7_53 853 Sadler, T. D., & Zeidler, D. L. (2004). The morality of socioscientific issues: Construal and 854 resolution of genetic engineering dilemmas. Science Education, 88(1), 4–27. 855 https://doi.org/10.1002/sce.10101 856 Sadler, T. D., & Zeidler, D. L. (2005). The significance of content knowledge for informal 857 reasoning regarding socioscientific issues: Applying genetics knowledge to genetic 858 engineering issues. Science Education, 89(1), 71–93. https://doi.org/10.1002/sce.20023 STUDENT ATTITUDES ON GENETICS

859 Shaw, K. R. M., Horne, K. Van, Zhang, H., & Boughman, J. (2008). Essay Contest Reveals 860 Misconceptions of High School Students in Genetics Content. Genetics, 178, 1157–1168. 861 https://doi.org/10.1534/genetics.107.084194 862 Shostak, S., Freese, J., Link, B. G., & Phelan, J. C. (2009). The politics of the gene: Social status 863 and beliefs about genetics for individual outcomes. Social Psychology Quarterly, 72(1), 77–93. 864 https://doi.org/10.1177/019027250907200107 865 Sjaastad, J. (2013). Measuring the ways significant persons influence attitudes towards science and 866 mathematics. International Journal of Science Education, 35(2), 192–212. 867 https://doi.org/10.1080/09500693.2012.672775 868 Smith, M., & Gericke, N. (2013). Mendel in the modern classroom. Science & Education. 869 https://doi.org/10.1007/s11191-013-9629-y 870 Snell, K., & Tarkkala, H. (2019). Questioning the rhetoric of a “willing population” in Finnish 871 biobanking. Life Sciences, Society and Policy, 15(1), 4. https://doi.org/10.1186/s40504-019- 872 0094-5 873 Šorgo, A., & Ambrožič-Dolinšek, J. (2010). Knowlege of, attitudes toward, and acceptance of 874 genetically modified organisms among prospective teachers of biology, home economics, and 875 grade school in Slovenia. Biochemistry and Molecular Biology Education, 38(3), 141–150. 876 https://doi.org/10.1002/bmb.20377 877 Sturgis, P., Brunton-Smith, I., & Fife-Schaw, C. (2010). Public attitudes to genomic science: An 878 experiment in information provision. Public Understanding of Science, 19(2), 166–180. 879 https://doi.org/10.1177/0963662508093371 880 Team, R. C. (2013). R: A language and environment for statistical computing. Vienna, Austria.: R 881 Foundation for Statistical Computing. Retrieved from http://www.r-project.org/ 882 Tidemand, S., & Nielsen, J. A. (2017). The role of socioscientific issues in biology teaching: from 883 the perspective of teachers. International Journal of Science Education, 39(1), 44–61. 884 https://doi.org/10.1080/09500693.2016.1264644 885 Uitto, A. (2014). Interest, attitudes and self-efficacy beliefs explaining upper-secondary school 886 students’ orientation towards biology-related careers. International Journal of Science and 887 Mathematics Education, 12(6), 1425–1444. https://doi.org/10.1007/s10763-014-9516-2 888 van den Ham, A.-K., & Heinze, A. (2018). Does the textbook matter? Longitudinal effects of 889 textbook choice on primary school students’ achievement in mathematics. Studies in 890 Educational Evaluation, 59, 133–140. 891 https://doi.org/https://doi.org/10.1016/j.stueduc.2018.07.005 892 Yen, W. M. (1984). Effects of local item dependence on the fit and equating performance of the 893 three-parameter logistic model. Applied Psychological Measurement, 8(2), 125–145. 894 https://doi.org/10.1177/014662168400800201

895 STUDENT ATTITUDES ON GENETICS

896 Table 1: The sample size from different schools, teachers with different teaching emphasis and used 897 textbook. Teacher Number of Teacher emphasis in Used textbook

student genetics teaching

answers

A 25 Developmental Textbook 1

B 49 Developmental Textbook 1

C 53 Hereditary Textbook 1

D 47 Hereditary Textbook 1

E 42 Structural Textbook 1

F 19 Developmental Textbook 1

H 65 Structural Textbook 2

I 55 Hereditary Textbook 1

J 37 Developmental Textbook 1

K 29 Developmental Textbook 2

898 STUDENT ATTITUDES ON GENETICS

899 Table 2: Correlations among different factors. Values shown with 95% confidence intervals. Attitude towards Beliefs in Experiencing Self-concept in

gene technology genetic utility in genetics

determinism genetics

Beliefs in genetic 0.17

determinism (0.04-0.30)

Experiencing utility in 0.38 0.26

genetics (0.27-0.50) (0.09-0.43)

Self-concept in genetics 0.12 0.24 0.55

(0.06-0.18) (0.12-0.36) (0.49-0.61)

Liking genetics 0.31 0.44 0.77 0.73

(0.21-0.40) (0.36-0.52) (0.74-0.80) (0.65-0.81)

900 STUDENT ATTITUDES ON GENETICS

901 902 Figure 1: The distribution of the responses for each of the items included in the final scale. The 903 items are grouped by factors to which they belong (left side). The value in the middle of the bar 904 represents the mean for each item (from 1 = strongly disagree to 5 = strongly agree). The item- 905 related statistics are shown in Table S1 and S2. For the analysis, the items marked with R were 906 reversed and the items in italics performed poorly and were removed. STUDENT ATTITUDES ON GENETICS

907

908

909 Figure 2: Links between student- and teacher-related variables and student attitudes. For each 910 variable, one level is chosen as a baseline (Textbook 1, developmental emphasis of the teacher and 911 female students) and this is represented by unfilled circles. Differences from baselines is directly 912 comparable to differences in responses to survey. Values substantially differing from baseline as 913 shown with 95% confidence intervals are colored black, while values with no significant difference 914 from baseline are colored gray.

915 STUDENT ATTITUDES ON GENETICS

916 Table S1: Exploratory Factor Analysis results for all the initial items. Rotated factors loadings are shown for five 917 factors: F1 matches to “Liking genetics”, F2 to “Attitudes towards gene technology” F3 to “Belief in genetic 918 determinism”, F4 to “Experiencing utility of genetics”, and F5 to “Self-concept in genetics”. Communality (h2) is 919 shown for all initial items. Items 6, 14, 17, 20, 23 and 24 were dropped from Confirmatory Factor Analysis. Items in 920 italics are inversed. Item Statement F1 F2 F3 F4 F5 h2 1 Genetics is a difficult field of biology 0.01 -0.02 -0.07 -0.03 0.61 0.36 2 Modification of human genomes is -0.08 0.36 -0.06 -0.04 -0.02 0.11 ethically acceptable if it allows for curing genetic disorders. 3 Genes determine all the traits in humans -0.03 0.10 -0.27 0.07 -0.01 0.08 4 Genetically modified plants will help to -0.04 0.31 0.02 0.19 -0.01 0.09 reduce famine in the world. 5 It is boring to study genetics 0.67 0.01 -0.16 -0.01 -0.01 0.54 6 It is impossible for me to reach good 0.19 0.18 0.29 0.06 0.31 0.51 results in genetics. 7 I need knowledge on genetics in my -0.02 -0.01 -0.04 0.70 0.09 0.49 future studies. 8 If the genome of a person is known, we 0.08 0.02 -0.45 -0.01 -0.03 0.19 know exactly which diseases they will have. 9 I think I excel in genetics. 0.23 0.01 0.01 0.01 0.53 0.42 10 Stem cell research done on human -0.04 0.32 0.04 0.07 -0.02 0.12 embryo should be illegal. 11 Human intelligence is determined by -0.10 -0.04 -0.30 -0.06 0.13 0.14 their genes. 12 I do not need in future what I have 0.02 0.02 0.04 0.76 -0.06 0.61 studied in genetics course so far 13 Usually we have interesting exercises in 0.72 -0.10 0.05 -0.04 - 0.04 0.42 genetics. 14 Genetics literacy is required in everyday 0.24 -0.08 -0.04 0.16 -0.06 0.09 life. 15 Many things in genetics are difficult. -0.14 0.02 0.07 0.03 0.57 0.30 16 I like to study genetics. 0.77 0.01 0.07 0.15 0.05 0.84 17 Studying human genomes leads to -0.02 -0.01 0.20 -0.01 0.03 0.04 parents selecting offspring who is genetically favorable. 18 I can solve even difficult genetics 0.19 0.03 0.10 0.07 0.37 0.37 exercises. 19 I think knowing genetics is important. 0.19 0.01 0.01 0.30 -0.07 0.31 20 The effect of genes on human happiness 0.01 -0.07 0.01 0.01 -0.02 0.01 is marginal. 21 Genetics is one of my favorite topics in 0.53 0.06 -0.04 -0.03 0.13 0.37 biology 22 It is acceptable that scientists develop 0.08 0.23 -0.04 -0.05 -0.09 0.25 deadlier pathogens in laboratory through genetic modificatino if that allows for new cures to diseases. 23 Understanding genetics is more and more 0.30 0.27 0.02 0.07 -0.11 0.24 important in the future. 24 There are genetic factors in parents that -0.07 0.05 -0.01 0.03 -0.04 0.01 predispose their children to be good in school. 25 I like biology lessons where we discuss 0.90 0.05 - 0.06 0.01 0.03 0.85 genetics. 921 922 STUDENT ATTITUDES ON GENETICS

923 Table S2: Confirmatory Factor Analysis results for all the initial items. Factors loadings and communality (h2) are 924 shown for five factors for each items.

I Statement

ity

2

SX

concept in

2

-

2 SCX

Attitudes towards gene technology Belief in genetic determinism Experiencing util in genetics Self genetics Liking genetics h RMSEA p 1 Genetics is a difficult field of biology 0.45 0.20 0.02 0.36 2 Modification of human genomes is 0.33 0.11 0.03 0.09 ethically acceptable if it allows for curing genetic disorders. 3 Genes determine all the traits in 0.27 0.07 0.03 0.06 humans 4 Genetically modified plants will 0.32 0.10 0.01 0.66 help to reduce famine in the world. 5 It is boring to study genetics 0.71 0.51 0.03 0.09 7 I need knowledge on genetics in my 0.72 0.51 0.03 0.09 future studies. 8 If the genome of a person is known, 0.45 0.20 0.03 0.09 we know exactly which diseases they will have. 9 I think I excel in genetics. 0.77 0.60 0.03 0.06 10 Stem cell research done on human 0.30 0.09 0.01 0.41 embryo should be illegal. 11 Human intelligence is determined by 0.29 0.08 0.03 0.09 their genes. 12 I do not need in future what I have 0.78 0.61 0.03 0.09 studied in genetics course so far 13 Usually we have interesting 0.63 0.39 0.03 0.06 exercises in genetics. 15 Many things in genetics are difficult. 0.38 0.15 0.01 0.48 16 I like to study genetics. 0.91 0.83 0.03 0.10 18 I can solve even difficult genetics 0.64 0.41 0.02 0.22 exercises. 19 I think knowing genetics is 0.47 0.22 0.03 0.10 important. 21 Genetics is one of my favorite topics 0.57 0.34 0.01 0.47 in biology 22 It is acceptable that scientists 0.20 0.05 0.01 0.78 develop deadlier pathogens in laboratory through genetic modification if that allows for new cures to diseases. 25 I like biology lessons where we 0.92 0.85 0.03 0.06 discuss genetics.

Factor empirical reliability 0.47 0.50 0.79 0.78 0.89 925

926