2. Methodology

to their personal goals and they are not aware of the usefulness of this knowledge in everyday life [9]. As students progress academically, they begin to consider that science subjects are complex and boring [10]. Other authors [11] add that students show low motivation and mood in learning activities related to STEM areas. This can be linked to the methodologies and teaching strategies used in science classrooms [12]. Similarly, reports from the Organisation for Economic Cooperation and Development [1] state that young people are not able to solve scientific problems in creative and innovative ways and experience difficulties in addressing activities and challenges associated with the areas of science and technology. This may be associated with a lack of motivation for learning [13] or even with the emotions the students experience toward learning science [14]. With respect to emotional domain, it should be noted that several studies relate it both to cognitive domain and to the concept of self-efficacy presented by the students [15]. According to some authors [16], students' perception of their self-efficacy in scientific-

technological subjects predicts their performance in these areas. Beliefs of academic self-efficacy shape students'school and professional aspirations [17]. That is, successful performance improves the perception of self-efficacy and the expectation of positive results, thus strengthening the interests and goals to be achieved [18, 19]. Students will show higher rates of self-efficacy if they show concentration, control, happiness, participation, and satisfaction during school work [20, 15]. However, academic and competency performance is lower as a negative view of addressing

Although students' interest and positive attitudes in science diminish throughout schooling [22], STEM interdisciplinary programs can provide the time and space needed to address this decline in scientific vocations and commitment [23]. Specifically, various studies [24] suggest that STEM competencies should be encouraged from an early age by using innovative teaching strategies that encourage the internalization of content so that it is maintained over the long term. In addition, it is more feasible to implement an integrated curriculum of these subjects in primary education because students spend most of their school time with their tutor teacher. Thus, an interdisciplinary and integrated treatment of STEM competencies would not negatively affect the educational process at these levels [25]. STEM education requires alternative didactic strategies to traditional teaching aimed at promoting a more valid and useful school science that involves students in improving their STEM skills [26]. Thus, for example, scientific models and theories will become relevant for students if they are given opportunities to test their usefulness and explanatory potential [27, 28]. The inclusion of STEM experiences in the curriculum at the primary education stage can improve the understanding of the youngest toward the diverse scientific-technological roles of society, as well as improve involvement, motivation, and the search for solutions to real problems by contextualizing mathematics, technology, engineering, and science contents [29]. Schools that offer STEM-focused programs have become the center of several policy initiatives and research projects [30]. Results from some studies [31] indicate that students' intention to specialize in one of the STEM areas or the likelihood that students will choose a STEM major is positively correlated with attendance at schools with STEM educational programs. Many educators believe that schools with a STEM approach will promote the preparation of well-informed citizens who have access to and appreciation of the ideas and tools of science and engineering [32]. In addition, schools that focus on science, technology, and innovation are also an enabling strategy for closing racial and gender gaps in learning opportunities in these fields [33]. In addition, these educational programs offer students the opportunity to have more information about STEM disciplines and greater academic and

their learning process is higher [21].

Theorizing STEM Education in the 21st Century

employment opportunities [31].

12

#### 2.1 Research design

This research is based on two parallel studies focused on STEM education in the function of diverse variables related to cognitive, affective, and competency aspects.

Study 1 has been oriented to analyze the cognitive and affective dimensions that primary education students present toward STEM areas, following an exploratory research design with a mixed analysis of the obtained data.

Study 2 has been aimed at validating the implementation of STEM workshops in the primary education classroom, following a quasi-experimental research design with pretest, posttest, control, and experimental groups, analyzing both cognitive and affective variables.

#### 2.2 Objectives

The research carried out has pursued two general objectives based on the two studies proposed:

General objective 1 (study 1): to analyze the cognitive, affective, and competency dimensions of primary school students in relation to STEM areas. General objective 2 (study 2): to implement and validate STEM workshops as active didactic strategies that improve the teaching/learning of these areas in primary school students.

#### 2.3 Hypothesis

The general objectives have served as a reference for formulating the following research hypotheses:

Hypothesis 1 (H1): elementary students have a low level of knowledge in STEM areas.

Hypothesis 2 (H2): there are differences in the level of knowledge in STEM areas of the primary students depending on the variable academic level. Hypothesis 3 (H3): there are no statistically significant differences in the level

of knowledge in STEM areas as a function of the gender variable. Hypothesis 4 (H4): primary school students show a favorable attitude toward STEM subjects and their learning.

Hypothesis 5 (H5): elementary students have low levels of proficiency in STEM areas.

Hypothesis 6 (H6): there are no statistically significant differences in competency values with respect to the gender variable.

Hypothesis 7 (H7): the implementation of STEM workshops in the primary classroom as didactic strategies produces a cognitive and emotional evolution in the students.

Hypothesis 8 (H8): there are statistically significant differences in cognitive and affective variables between the students who use a traditional methodology and those who use a methodology based on the implementation of STEM workshops.

Hypotheses 1–6 are checked in Study 1 and hypotheses 7 and 8 in Study 2.

#### 2.4 Sample

The sample was selected through a random process, involving 1256 primary school students. Since the two general objectives were set according to the two studies, the sample participating in the research was divided into two subsamples.

Subsample 1 consisted of 801 pupils aged between 8 and 12 from different schools. This group was used for Study 1 with an exploratory character on cognitive, affective, and competence variables.

> section of the questionnaire had the purpose of assessing the level of STEM knowledge of the students by means of 10 multiple choice questions about theoretical contents or situations of application of the contents. The content of these 10 questions is based on the education curriculum of the primary stage. Table 1 shows some of the

receives?

mixed

liquid state

when we use it

Table 2 shows some questions from the second section aimed at assessing the

For Study 2 on the validation and implementation of STEM workshops with subsample 2, various questionnaires were designed according to the workshop topic. Specifically, for each workshop, one was developed as a pretest to evaluate the initial level of knowledge of the participating sample and another as a posttest to check whether student learning improved after the explanation of the contents by means of the two didactic methodologies used: that of the control group and that of the experimental group. The questions used in these questionnaires were based on the questions in the textbooks of the different publishers used by the students in the classroom. By way of example, one of the questions from workshop 3 is specified. "When approaching a traffic light, a cyclist stops pedaling. For a while, however, the bicycle continues to move. What causes the bicycle to stop after a certain time?"

3.1 Results of Study 1: analysis of the cognitive, affective, and competence dimensions of primary school students in relation to STEM areas

First, a descriptive analysis of the cognitive dimension is presented and then the inferential analysis is detailed in order to test the proposed research hypotheses. Next, the results related to the affective dimension and finally those related to the

affective and competence questions of the first section of the questionnaire.

Example of questions related to the affective and competence dimension

Implementation and Didactic Validation of STEM Experiences in Primary Education: Analysis…

7. Have you ever disassembled a toy to see

9. Laura's blender receives electricity from the grid by plugging it into an outlet. But into what do you think the mixer transforms the electricity it

a. In motion so that the ingredients are well

b. In heat so that the ingredients remain in a

c. In sound, that's why it makes so much noise

b. Yes, but it broke down c. No, but I'd like to do it

a. Yes, I wanted to see how it worked

what it's like inside?

d. Never

4. Do you like to learn science by doing experiments

DOI: http://dx.doi.org/10.5772/intechopen.88048

Example of questions related to the affective and competence dimension.

Example of questions related to the cognitive dimension

2. Julia and Henry are making a model with an electric circuit for school. What materials do they

a. A battery, a light bulb, a switch, and the

b. A wooden stand, a battery, and insulating

c. A battery, a light bulb, a conductor cable,

Example of questions related to the cognitive dimension.

need for the circuit to work?

conductor wires

and a wooden stand d. Two batteries and a switch

cables

and hands-on tasks? a. I love it b. I'm good at it c. I'm bad at it d. It bores me

Table 1.

Table 2.

level of STEM knowledge.

3. Results

15

competence dimension are represented.

Subsample 2 consisted of 455 students aged 10–12 from different schools. The students in each school were divided into two homogeneous groups, control and experimental according to the theme of the different STEM workshops implemented. This group was used for Study 2 with a quasi-experimental purpose to validate the didactic relevance of the implementation of the STEM workshops. The STEM contents worked on in the control groups and experimental groups have been the same and were selected from the education curriculum. The control groups (CG) have followed a methodology based on a more traditional teaching of the selected STEM contents, using as resources the textbooks and their specific worksheets. However, the experimental groups (EG) have followed a teaching methodology based on STEM workshops. This type of resources allows interdisciplinary work on diverse scientific, technological, and mathematical contents, as indicated in previous studies [37]. The workshops have been designed in such a way that they can be carried out in 2 or 3 classroom sessions. They consist of making a model with easily acquired or recycled materials to facilitate their reproduction in informal contexts. The construction of the model makes it possible to work on different contents of the STEM areas involved, which are selected from the primary education curriculum. In addition, they are accompanied by a video, a didactic guide, and an observation sheet for the students, in order to focus their attention on the contents worked on.

#### 2.5 Measuring instrument

Different measuring instruments have been designed and implemented according to the research objectives.

For Study 1 carried out with subsample 1, a questionnaire was designed divided into two sections (Questionnaire 1). The first section evaluated affective and competency aspects and consisted of 21 questions with 4 answer options. Some of the questions were aimed at verifying the degree of affectivity and appreciation of the student toward science in different contexts. Other questions asked were intended to diagnose the level of competence, capacity, or self-efficacy of the student participant in different real situations related to STEM tasks. As an initial diagnosis, the second

Implementation and Didactic Validation of STEM Experiences in Primary Education: Analysis… DOI: http://dx.doi.org/10.5772/intechopen.88048


#### Table 1.

Hypothesis 5 (H5): elementary students have low levels of proficiency in STEM

Hypothesis 6 (H6): there are no statistically significant differences in

those who use a methodology based on the implementation of STEM

Hypotheses 1–6 are checked in Study 1 and hypotheses 7 and 8 in Study 2.

The sample was selected through a random process, involving 1256 primary school students. Since the two general objectives were set according to the two studies, the sample participating in the research was divided into two subsamples. Subsample 1 consisted of 801 pupils aged between 8 and 12 from different schools. This group was used for Study 1 with an exploratory character on cognitive,

Subsample 2 consisted of 455 students aged 10–12 from different schools. The students in each school were divided into two homogeneous groups, control and

implemented. This group was used for Study 2 with a quasi-experimental purpose to validate the didactic relevance of the implementation of the STEM workshops. The STEM contents worked on in the control groups and experimental groups have been the same and were selected from the education curriculum. The control groups (CG) have followed a methodology based on a more traditional teaching of the selected STEM contents, using as resources the textbooks and their specific worksheets. However, the experimental groups (EG) have followed a teaching methodology based on STEM workshops. This type of resources allows interdisciplinary work on diverse scientific, technological, and mathematical contents, as indicated in previous studies [37]. The workshops have been designed in such a way that they can be carried out in 2 or 3 classroom sessions. They consist of making a model with easily acquired or recycled materials to facilitate their reproduction in informal contexts. The construction of the model makes it possible to work on different contents of the STEM areas involved, which are selected from the primary education curriculum. In addition, they are accompanied by a video, a didactic guide, and an observation sheet for the students, in order to focus their attention on

Different measuring instruments have been designed and implemented

For Study 1 carried out with subsample 1, a questionnaire was designed divided into two sections (Questionnaire 1). The first section evaluated affective and competency aspects and consisted of 21 questions with 4 answer options. Some of the questions were aimed at verifying the degree of affectivity and appreciation of the student toward science in different contexts. Other questions asked were intended to diagnose the level of competence, capacity, or self-efficacy of the student participant in different real situations related to STEM tasks. As an initial diagnosis, the second

experimental according to the theme of the different STEM workshops

Hypothesis 7 (H7): the implementation of STEM workshops in the primary classroom as didactic strategies produces a cognitive and emotional evolution in

Hypothesis 8 (H8): there are statistically significant differences in cognitive and affective variables between the students who use a traditional methodology and

competency values with respect to the gender variable.

Theorizing STEM Education in the 21st Century

areas.

the students.

workshops.

affective, and competence variables.

the contents worked on.

14

2.5 Measuring instrument

according to the research objectives.

2.4 Sample

Example of questions related to the affective and competence dimension.


#### Table 2.

Example of questions related to the cognitive dimension.

section of the questionnaire had the purpose of assessing the level of STEM knowledge of the students by means of 10 multiple choice questions about theoretical contents or situations of application of the contents. The content of these 10 questions is based on the education curriculum of the primary stage. Table 1 shows some of the affective and competence questions of the first section of the questionnaire.

Table 2 shows some questions from the second section aimed at assessing the level of STEM knowledge.

For Study 2 on the validation and implementation of STEM workshops with subsample 2, various questionnaires were designed according to the workshop topic. Specifically, for each workshop, one was developed as a pretest to evaluate the initial level of knowledge of the participating sample and another as a posttest to check whether student learning improved after the explanation of the contents by means of the two didactic methodologies used: that of the control group and that of the experimental group. The questions used in these questionnaires were based on the questions in the textbooks of the different publishers used by the students in the classroom. By way of example, one of the questions from workshop 3 is specified. "When approaching a traffic light, a cyclist stops pedaling. For a while, however, the bicycle continues to move. What causes the bicycle to stop after a certain time?"

#### 3. Results

#### 3.1 Results of Study 1: analysis of the cognitive, affective, and competence dimensions of primary school students in relation to STEM areas

First, a descriptive analysis of the cognitive dimension is presented and then the inferential analysis is detailed in order to test the proposed research hypotheses. Next, the results related to the affective dimension and finally those related to the competence dimension are represented.

#### 3.1.1 Cognitive dimension analysis

The descriptive statistics obtained by subsample 1 (n = 801 students) in the knowledge questionnaire are presented. Primary school students score an average of 5.38 points out of 10, with a standard deviation of 1.72. Although the score obtained suggests that students show knowledge about STEM content, the analysis by questions reveals that the level of knowledge is worse when it comes to answering purely theoretical questions. However, students scored better on content-related questions about real situations, coinciding with other studies [38, 9].

Table 3 shows the descriptive statistics obtained in the STEM level of knowledge of primary school students according to the variable academic level.

As can be seen in Table 3, third-grade students score an average of 4.82 points out of 10; fourth-grade students score 5.46 points; fifth-grade students average 5.44 points; and sixth-grade students average 5.74 points. Regardless of the academic year, the cognitive level of the students is not very high, although it is true that there is a cognitive improvement with academic progress. However, the results obtained allow us to accept Hypothesis 1 "Elementary students have a low level of knowledge in STEM areas." In order to verify the existence of statistically significant differences depending on the variable academic level, an ANOVA statistical test of one factor with Tukey's post hoc has been carried out. The results obtained are shown in Tables 4 and 5.

On the other hand, it is intended to analyze the influence of gender on the variable level of knowledge due to the numerous existing stereotypes in relation to the subject. Specifically, some authors [40] point out that girls outnumber boys when it comes to participating in class and doing homework, but boys do better on physics tests. Other studies [41] indicate that gender differences can be reduced with a value affirming intervention. On the other hand, [42] indicate that the gender gap in STEM disciplines goes beyond the limited representation of women since women actually score lower on exams and on standardized tests on scientific concepts. Other authors [43] also agree that women show a greater preference for studies related to the health sector (nursing, veterinary, or microbiology) and men choose careers such as architecture, engineering, physics, or computer science. Table 6 shows the descriptive statistics according to the gender variable.

Men 5.47 1.74 0.10 Women 5.32 1.69 0.10

As can be seen in Table 6, boys score an average of 5.47 points with a standard deviation of 1.74. On the other hand, girls achieve a score of 5.32 points with a standard deviation of 1.69 points. These results seem to indicate that in the exploratory study carried out with subsample 1 (primary school students) there is STEM knowledge equity regardless of gender. Nevertheless, it was thought convenient to validate this assertion by means of an inferential analysis. Table 7 shows the Stu-

As can be seen in Table 7, the value of the significance obtained was Sig. = 0.305, so we can accept Hypothesis 3 "There are no statistically significant differences in the

T Df Sig. (2-tailed) Mean difference Std. error difference 95% confidence

Mean 1.026 548 0.305\* 0.150 0.146 0.137 0.438

level of knowledge in STEM areas as a function of the gender variable."

dent's t-test carried out.

Student's t-test (variable: gender).

\* Sig. < 0.05.

17

Table 7.

(I) School year

\* Sig. < 0.05.

Table 5.

Table 6.

Descriptive statistics (gender).

(J) School year

DOI: http://dx.doi.org/10.5772/intechopen.88048

Tukey's HSD post hoc test (academic level).

Mean difference (I-J)

3rd PE 4th PE 0.638 0.189 0.005\* 1.126 0.149

Implementation and Didactic Validation of STEM Experiences in Primary Education: Analysis…

Std. error

6th PE 0.917 0.203 0.000\* 1.442 0.392

Mean Std. deviation Std. error of the mean

Sig. 95% confidence interval Lower bound

Upper bound

interval of the difference Lower Upper

The data presented in Table 4 show the existence of statistically significant differences in the STEM cognitive domain between academic courses obtaining a significance of 0.001. The analysis with Tukey's post hoc shown in Table 5 indicates that these differences in the variable level of knowledge appear among third vs. fourth graders (Sig. = 0.005) and among third graders vs. sixth graders (Sig. = 0.000), favoring the average score to students in the upper grades in both cases. It seems evident that the STEM contents are dealt with in greater depth in the more advanced courses; however, it is necessary to pay attention to the didactic strategies used to avoid forgetting in the higher courses [39]. On the other hand, the data presented above make it possible to accept Hypothesis 2 "There are differences in the level of knowledge in STEM areas of the primary students depending on the variable academic level."


#### Table 3.

Descriptive statistics (academic level).


#### Table 4.

One-factor ANOVA test (academic level).

Implementation and Didactic Validation of STEM Experiences in Primary Education: Analysis… DOI: http://dx.doi.org/10.5772/intechopen.88048


#### Table 5.

3.1.1 Cognitive dimension analysis

Theorizing STEM Education in the 21st Century

shown in Tables 4 and 5.

variable academic level."

Descriptive statistics (academic level).

One-factor ANOVA test (academic level).

Table 3.

\* Sig. < 0.05.

16

Table 4.

The descriptive statistics obtained by subsample 1 (n = 801 students) in the knowledge questionnaire are presented. Primary school students score an average of 5.38 points out of 10, with a standard deviation of 1.72. Although the score obtained suggests that students show knowledge about STEM content, the analysis by questions reveals that the level of knowledge is worse when it comes to answering purely theoretical questions. However, students scored better on content-related questions

Table 3 shows the descriptive statistics obtained in the STEM level of knowledge

As can be seen in Table 3, third-grade students score an average of 4.82 points out of 10; fourth-grade students score 5.46 points; fifth-grade students average 5.44 points; and sixth-grade students average 5.74 points. Regardless of the academic year, the cognitive level of the students is not very high, although it is true that there is a cognitive improvement with academic progress. However, the results obtained allow us to accept Hypothesis 1 "Elementary students have a low level of knowledge in STEM areas." In order to verify the existence of statistically significant differences depending on the variable academic level, an ANOVA statistical test of one factor with Tukey's post hoc has been carried out. The results obtained are

The data presented in Table 4 show the existence of statistically significant differences in the STEM cognitive domain between academic courses obtaining a significance of 0.001. The analysis with Tukey's post hoc shown in Table 5 indicates that these differences in the variable level of knowledge appear among third vs.

(Sig. = 0.000), favoring the average score to students in the upper grades in both cases. It seems evident that the STEM contents are dealt with in greater depth in the more advanced courses; however, it is necessary to pay attention to the didactic strategies used to avoid forgetting in the higher courses [39]. On the other hand, the data presented above make it possible to accept Hypothesis 2 "There are differences in the level of knowledge in STEM areas of the primary students depending on the

School year Mean Std. deviation Std. error of the mean

ANOVA Sum of squares Df Mean square F Sig. Average score Between groups 61.775 3 20.592 7.111 0.001\* Within groups 1595.479 551 2.896

Total 1657.254 554

3rd PE 4.82 1.59 0.13 4th PE 5.46 1.71 0.11 5th PE 5.44 1.50 0.18 6th PE 5.74 1.84 0.15

fourth graders (Sig. = 0.005) and among third graders vs. sixth graders

about real situations, coinciding with other studies [38, 9].

of primary school students according to the variable academic level.

Tukey's HSD post hoc test (academic level).


#### Table 6.

Descriptive statistics (gender).

On the other hand, it is intended to analyze the influence of gender on the variable level of knowledge due to the numerous existing stereotypes in relation to the subject. Specifically, some authors [40] point out that girls outnumber boys when it comes to participating in class and doing homework, but boys do better on physics tests. Other studies [41] indicate that gender differences can be reduced with a value affirming intervention. On the other hand, [42] indicate that the gender gap in STEM disciplines goes beyond the limited representation of women since women actually score lower on exams and on standardized tests on scientific concepts. Other authors [43] also agree that women show a greater preference for studies related to the health sector (nursing, veterinary, or microbiology) and men choose careers such as architecture, engineering, physics, or computer science. Table 6 shows the descriptive statistics according to the gender variable.

As can be seen in Table 6, boys score an average of 5.47 points with a standard deviation of 1.74. On the other hand, girls achieve a score of 5.32 points with a standard deviation of 1.69 points. These results seem to indicate that in the exploratory study carried out with subsample 1 (primary school students) there is STEM knowledge equity regardless of gender. Nevertheless, it was thought convenient to validate this assertion by means of an inferential analysis. Table 7 shows the Student's t-test carried out.

As can be seen in Table 7, the value of the significance obtained was Sig. = 0.305, so we can accept Hypothesis 3 "There are no statistically significant differences in the level of knowledge in STEM areas as a function of the gender variable."


Table 7. Student's t-test (variable: gender).
