INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 42

www.rsisinternational.org

Effectiveness of Rasberry Pi-Based Laboratory on Students’ Attitude

Towards STEM among Pre-University Students

Aslindawati Binti Abdullah

, Nurul Syafiqah Yap Abdullah

, Eko Nursulistiyo

1,2

Department of Physics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris,

35900 Tanjong Malim, Perak, Malaysia

Faculty of Teacher Training and Education, Ahmad Dahlan University, Jl. Kapas No.9, Semaki, Kec.

Umbulharjo, Kota Yogyakarta, Daerah Istimewa Yogyakarta 55166, Indonesia.

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.927000006

Received: 12 November 2025; Accepted: 18 November 2025; Published: 26 November 2025

ABSTRACT

This study investigated the effectiveness of the Raspberry Pi-Assisted Physics Laboratory for Pre-University

Students (Rasphy) in enhancing students’ attitudes toward STEM with a specific emphasis on science,

technology, engineering and mathematics. This study employed Kolb’s Experiential Learning Theory as the

theoretical foundation for a twelve-week intervention involving 134 pre-university students. During this period,

participants engaged in five structured, hands-on Electricity experiments using Raspberry Pi microcomputers.

The Rasphy learning environment integrated real-world applications such as circuit construction and data

logging to encourage active learning and critical thinking. A quasi-experimental one-group pre-test, post-test and

delayed post-test design was utilised. Inferential analysis through repeated-measures MANOVA revealed a

significant main effect of time (Wilks’ Lambda = 0.376, F(6,128) = 35.48, p < 0.001). Post-hoc Bonferroni tests

confirmed sustained improvements in students’ attitudes across all STEM domains. Large effect sizes were

recorded for engineering (η² = 0.39), technology (η² = 0.41), science (η² = 0.33), and mathematics (η² = 0.31).

Notably, the minimum attitude score in engineering increased from 2.00 to 3.40 after the intervention. The

findings demonstrate that the Rasphy laboratory effectively fostered conceptual understanding and more positive

STEM attitudes through immersive and experiential activities. This study provides empirical support for

integrating low-cost digital technologies like Raspberry Pi in pre-university physics education to cultivate STEM

interest, enhance motivation and develop 21st-century skills.

Keywords: Physics, Raspberry Pi, Attitude Towards STEM, pre-university

INTRODUCTION

The rapid advancement of technology in recent decades has significantly transformed the landscape of education

and as a result, teaching and learning are no longer confined to traditional methods but have evolved to embrace

digital tools, automation, as well as data-driven approaches. In this transformation, science, technology,

engineering and mathematics (STEM) have emerged as core pillars, shaping not only what students learn, but

also how they are prepared to meet the demands of a fast-changing and innovation-driven future. Physics, as one

of the foundational pillars within the STEM disciplines, plays a critical role in cultivating scientific literacy,

analytical reasoning and problem-solving skills that are essential for navigating the demands of modern

technological society. Despite its significance, a substantial number of students continue to perceive physics as

a challenging and abstract subject. This perception is often exacerbated by pedagogical approaches that rely

heavily on rigid, didactic instruction, which tends to prioritise formulaic problem-solving over conceptual

understanding and meaningful engagement. The lack of experiential based learning opportunities further

compounds this issue, particularly when students are not provided with adequate exposure to hands-on laboratory

activities that bridge theory and real-world application. Research by Spaan et al. (2022) underscores the value

of active learning environments, highlighting that students develop deeper conceptual understanding when they

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 43

www.rsisinternational.org

are encouraged to engage in practical investigations, collaborative discussions and experiential tasks that involve

exploring real phenomena.

Despite the acknowledged benefits of conventional laboratory instruction in science education, several persistent

challenges continue to hinder its effectiveness. Traditional lab settings often require high levels of abstract

reasoning and cognitive processing, which may exceed the developmental readiness of many pre-university

learners. When laboratory tasks are delivered in a manner that is overly procedural, lecture-driven or lacking in

meaningful student interaction, learners may struggle to grasp the conceptual significance of the activities they

are performing. This disconnect not only impairs comprehension but can also diminish students’ motivation and

engagement in physics learning (Faridi et al., 2021; Chambers, 2014). Raspberry Pi microcomputer can be

employed to address existing pedagogical limitations in physics laboratory instruction for pre-university

students. By embedding Raspberry Pi into practical lab activities, this study aims to enhance the authenticity and

relevance of learning experiences, enabling students to engage directly in programming, data acquisition, circuit

construction and real-time problem solving. These activities not only simulate real-world engineering practices

but also promote active learning, improve conceptual understanding and bridge the persistent gap between

theoretical knowledge and practical application (Ariza & Baez, 2022; Hatta & Budiyanto, 2021).

The advancement of microcomputer technologies such as the Raspberry Pi has opened new possibilities for

conducting science and engineering experiments across various levels of education (Balon & Simić, 2019). As

noted by Mahmood et al. (2019), microcomputers are particularly well-suited for laboratory-based learning due

to their affordability, portability, and accessibility. In Raspberry Pi-assisted laboratory environments, the

instructional approach emphasises hands-on engagement and collaborative learning, allowing students to

actively explore scientific concepts and collaboratively develop solutions to learning challenges through

groupbased discussions. Such an approach not only fosters deeper conceptual understanding but also cultivates

positive attitudes towards STEM, enhances essential 21st-century skills and encourages students to articulate

their ideas and share their findings with peers in meaningful ways. Practical learning, in this context serves as

an instructional strategy that empowers students to interact directly with technological tools through processes

such as creating, constructing, designing and analysing scientific experiments (Idris & Idris, 2020). Prasetya,

Hirashima and Hayashi (2020) observed that students often favour open-ended experimental tasks, as these

provide opportunities to address real-world problems while developing their own solutions. Nevertheless, the

integration of open-ended practices in science instruction remains limited (Hoehn et al., 2021), largely due to

the continued reliance on static instructional tools such as whiteboards and conventional laboratory manuals,

which dominate many traditional classroom and laboratory setting.

One of the persistent challenges in the teaching and learning of Physics, particularly in abstract topics such as

Electricity, lies in the difficulty of delivering complex scientific concepts through conventional instructional

methods. When teaching remains predominantly teacher-centred, students’ depth of conceptual understanding is

often compromised (Makhrus, Wahyudi, & Zuhdi, 2021; Fullan & Langworthy, 2013). This pedagogical

limitation frequently leads to the development and reinforcement of misconceptions, which may persist over

time, especially in topics where key phenomena such as electrical energy transfer are not directly observable.

The mastery of foundational electrical concepts is crucial, as it serves as the cognitive base from which students

construct scientific meaning and achieve desired learning outcomes. The concept of electricity occupies a central

position in the study of Physics, not only as a foundational scientific principle but also as a critical gateway to

understanding the mechanisms that govern both the natural and technological world. The fundamental principles

of electricity form the backbone of countless modern innovations across diverse sectors, including industrial

automation, domestic appliances, advanced manufacturing systems, robotics and medical technologies such as

diagnostic imaging and radiology (Voo, Hemani, & Cassidy, 2022). In light of the accelerating global shift

towards technology-intensive industries, the need for a scientifically literate and technically proficient workforce

has become more pressing than ever. As such, cultivating a robust conceptual understanding of electricity and

its real-world applications is essential for preparing students to meet the demands of the 21st-century knowledge

economy.Despite its significance, the teaching of Physics particularly the topic of Electricity is often delivered

in disciplinary silos, separate from mathematics, engineering and technological contexts (Naukkarinen & Bairoh,

2020; Mpofu, 2019; Ceylan & Ozdilek, 2015). This compartmentalised approach to instruction may impede

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 44

www.rsisinternational.org

students’ ability to construct integrated mental models of how scientific knowledge is applied across authentic,

interdisciplinary settings. Without explicit connections to related STEM domains, learners may struggle to

appreciate the broader utility of Physics beyond textbook content, thereby limiting their engagement and long-

term retention.

To foster deeper and more meaningful learning, it is therefore essential to adopt an integrative instructional

approach that weaves together key elements from mathematics, engineering and technology into the teaching of

Physics. As Valko and Osadchyi (2021) argue, STEM-integrated learning particularly when structured around

collaborative projects and problem-based activities offers students the opportunity to explore scientific concepts

with greater relevance, contextual depth, and personal agency. This pedagogical shift not only strengthens

students’ conceptual grasp of Physics but also enhances their motivation, curiosity and capacity to apply

scientific thinking in solving real world challenges.Attitude, within the educational context is commonly

understood as a psychological predisposition that influences how individuals evaluate, interpret and respond to

specific domains of learning. In the realm of STEM education, students’ attitudes play a vital role in shaping

their level of engagement, motivation and sustained participation in instructional activities. A learner’s attitude

towards STEM is not merely a passive reflection of interest or preference, but rather a dynamic factor that can

significantly impact their learning trajectory. Understanding and assessing students’ attitudes towards STEM is

crucial, not only as a means of predicting academic achievement but also for informing the development of

instructional strategies that are responsive to learners’ needs. Numerous studies have demonstrated that a positive

attitude toward learning is strongly correlated with improved academic performance, as it enhances students’

willingness to engage with complex subject matter and persist through learning challenges. Bakar (2022) notes

that conventional, teacher-centred instructional approaches when combined with the inherent complexity of

scientific concepts often contribute to the formation of negative attitudes among students toward science and

technology subjects. These attitudes are further exacerbated when learners are required to absorb large volumes

of abstract theoretical content within limited timeframes. As reported by Hacieminoglu (2016), such cognitive

overload can lead to increased resistance, disinterest, and anxiety, ultimately undermining students’ perceptions

of science as a meaningful and accessible field of study. Moreover, students who struggle to recall and apply

Physics concepts frequently exhibit a decline in their attitudes towards STEM. This shift in attitude can

negatively influence their motivation, engagement, and overall academic performance in science-related

subjects. Recognising this concern, the present study seeks to examine the potential of integrating Raspberry Pi

technology into the teaching and learning of Electricity within Physics laboratory settings.

Specifically, this research investigates the effectiveness of a Raspberry Pi-assisted instructional approach in

enhancing students’ attitudes towards STEM within the context of the pre-university Physics curriculum. This

emphasis stems from the understanding that cultivating positive attitudes towards STEM is a critical factor

influencing students’ academic success, long-term engagement and interest in Physics and related disciplines.

When learning is grounded in authentic, real-world contexts, students are more likely to find meaning in abstract

scientific concepts and develop a sense of ownership in their learning process.To support this aim, an integrated

STEM-based laboratory module on the topic of Electricity was designed, leveraging the capabilities of Raspberry

Pi to facilitate hands-on experimentation and inquiry. This instructional design promotes meaningful learning by

merging content and skills from the domains of science, technology, engineering, and mathematics. The module

not only seeks to improve conceptual understanding, but also aims to develop students’ abilities to plan, conduct,

and evaluate scientific investigations in a systematic manner.The rationale for implementing integrated STEM

learning lies in its demonstrated potential to improve academic achievement, foster more positive learning

attitudes, and nurture lifelong learning habits (Baran, Canbazoglu Bilici, Mesutoglu, & Ocak, 2019; Ravitz,

2010; Wang & Degol, 2013). Research has shown that instructional approaches which connect multiple

disciplines can enhance students’ comprehension and lead to deeper, more durable learning outcomes (Purzer,

Goldstein, Adams, Xie, & Nourian, 2015; Kuo Hung Tseng, 2011). Furthermore, integrated STEM approaches

offer interactive and engaging learning experiences that not only increase student enjoyment, but also

demonstrate the practical relevance of STEM knowledge to everyday life—ultimately enriching students’

understanding and strengthening their sense of purpose in pursuing STEM-related learning (Eugenijus, 2023).

In contrast, positive attitudes towards science are more likely to emerge when learning is anchored in experiential

learning approaches, where knowledge is constructed through direct experience, reflection, and active

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 45

www.rsisinternational.org

participation in meaningful tasks (Kolb, 1984; Dewey, 1938). Experiential learning allows students to internalise

scientific concepts by engaging in authentic problem-solving activities that closely mirror real-world contexts.

Therefore, science instruction should avoid relying solely on traditional, teacher-centered methods that

emphasise passive content delivery. When learning is not actively experienced or personally relevant, students

may become disengaged, perceiving the process as monotonous or disconnected from their abilities and

aspirations. This disengagement can eventually lead to the development of negative attitudes towards science.

Students with positive attitudes towards STEM are generally more motivated, inquisitive, and inclined to develop

knowledge and skills in science, technology, engineering and mathematics. Such attitudes contribute not only to

their academic engagement but also to their long-term ambition to pursue STEM related careers. In this regard,

experiential learning plays a pivotal role by making abstract concepts more accessible and personally

meaningful, thereby enhancing learning outcomes and students’ self-efficacy. However, Beier et al. (2019) found

that many high school and college students maintain negative perceptions of STEM careers, viewing them as

lacking in creativity and social interaction. This perception can discourage them from pursuing such paths despite

their academic potential. As such, understanding students’ attitudes towards STEM is imperative. As such,

gaining a deep understanding of students’ attitudes towards STEM is of critical importance. This insight enables

educators and relevant stakeholders to design and implement more engaging, experience-oriented learning

environments that resonate with students’ interests and foster sustained intrinsic motivation. Ultimately, the

integration of experiential learning strategies has the potential to significantly improve students’ attitudes

towards STEM, enhance their preparedness for future careers and contribute meaningfully to national efforts

aimed at advancing STEM education.

This study introduced an intervention through a Raspberry Pi-assisted laboratory setting, known as Rasphy.

Within this environment, pre-university students participated in five structured hands-on experiments centred on

the topic of Electricity, with the Raspberry Pi microcomputer serving as the core instructional tool. These

practical activities were designed not only to reinforce theoretical knowledge but also to actively engage students

and enhance their attitudes towards STEM. By immersing students in experience-based learning, the Rasphy

approach aimed to spark curiosity, build motivation and develop more positive perceptions of science,

technology, engineering and mathematics. In this study, students participated in Physics laboratory sessions that

emphasised the hands-on application of electrical concepts through the use of Raspberry Pi technology. These

sessions were conducted under the guidance of instructors who assumed the role of facilitators, in line with the

principles of Experiential Learning Theory. Through this approach, students were encouraged to engage with

real-world problems from various angles, enhancing their problem-solving capabilities and nurturing a more

positive disposition towards STEM related subjects. A positive attitude towards STEM is recognised as a critical

enabler in the effective integration of STEM elements within the teaching and learning process. Beyond

supporting the acquisition of scientific knowledge, such attitudes have been shown to cultivate deeper interest

and engagement in the fields of science, technology, engineering and mathematics (Forbes & Skamp, 2015). In

the context of this research, particular attention was given to examining the attitudes of pre-university students

towards STEM, with the understanding that positive attitudes often stem from meaningful exposure to

STEMrelated experiences (White & Harrison, 2012). These experiences play a crucial role in shaping students’

academic trajectories and influencing their aspirations to pursue careers in STEM fields. As such, gaining a deep

understanding of students’ attitudes towards STEM is of critical importance. This insight enables educators and

relevant stakeholders to design and implement more engaging, experience-oriented learning environments that

resonate with students’ interests and foster sustained intrinsic motivation. Ultimately, the integration of

experiential learning strategies has the potential to significantly improve students’ attitudes towards STEM,

enhance their preparedness for future careers and contribute meaningfully to national efforts aimed at advancing

STEM education.

MATERIALS AND METHOD

Research Design

The primary objective of the study was to examine the extent to which this experiential learning strategy could

influence students’ attitudes towards STEM, particularly by making Physics more relatable and meaningful. To

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 46

www.rsisinternational.org

investigate this, a quantitative quasi-experimental design was employed, utilising a one-group pre-test and

posttest model. This design allowed the researcher to assess changes in student attitudes over time within the

same group, thereby providing a clearer picture of the impact of the intervention. The intervention was guided

by Kolb’s Experiential Learning Theory, which emphasises that deep and meaningful learning occurs through a

continuous cycle of concrete experiences, reflective observation, abstract conceptualisation and active

experimentation. Through problem-based laboratory tasks that required students to apply and reflect upon

theoretical knowledge, the Rasphy module encouraged deeper understanding and stronger engagement with

STEM content. In this study, students’ attitudes towards STEM were measured across three specific domains:

attitudes towards science, attitudes towards mathematics and attitudes towards technology and engineering

Study Sample

The respondents in this study were 134 Physics students referring to students who demonstrated relatively weak

academic performance in the second semester and also obtained low marks in topical assessments, indicating

persistent difficulties in mastering the subject matter over time. Respondents were selected using purposive

sampling techniques and then the sample size was determined using convenience sampling techniques.

Research Instruments

This study utilizes the Attitude Towards STEM test, which consists of 26 objective questions (Unfried et al.,

2015). The scores of the subjects in this study on the pre-and post-tests are assessed using this test. Pre- and post-

tests, as well as advanced posts on the research, were administered over two hours prior to and following the

Raspberry Pi intervention in the laboratory on the topic of Electricity.

This study employed a quasi-experimental quantitative analysis involving respondents who received a one-group

pre- and post-test intervention over 12 weeks. Their experiences were measured quantitatively to determine the

effectiveness of the intervention carried out. There is no need for a control group in this study's design (Creswell,

2009). It is possible to determine the effectiveness of the intervention by considering all potential obstacles,

including the intervention itself. It takes at least eight weeks to reach maturity (Rasdi et al., 2021). Both

traditional classroom instruction and lab lessons utilizing a Raspberry Pi were used to teach the respondents

about electricity. This indicates that through experiential learning, survey respondents' conceptual understanding,

group experimentation skills, and perceptions of STEM are all altered. When people learn from their own

experiences, they become more self-assured and driven when discussing Electricity.

The respondents completed a pre-test using an attitude questionnaire towards STEM to measure their attitude

score towards STEM before they were involved in the intervention. Next, they were grouped through a Raspberry

Pi-based laboratory learning approach as an intervention for twelve weeks. After the intervention, the researcher

re-measured the respondents' attitude scores towards STEM in a post-test. The advanced post-test is conducted

four weeks after the study, where respondents answer the same questionnaire to assess the retention effect of

attitudes towards STEM after the study has been completed. The researcher conducted a differential analysis of

pre-test, post-test and advanced post-test score data concerning the intervention effect of this study.

RESULT AND DISCUSSION

Descriptive Analysis

Table 1 presents the descriptive statistics of the Mean, Standard Deviation, Minimum, Maximum, Skewness,

and kurtosis for the Pre-Test, Post-Test, and Advanced Post-Test of Attitudes Toward Science. Descriptive

statistical analysis was performed to identify the mean scores of pre-, post- and post-advanced questionnaires

for the variable of students' attitudes towards STEM. In addition, the values of standard deviation, minimum,

maximum, skewness and kurtosis are also displayed in Table 1.1

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 47

www.rsisinternational.org

Table 1. Descriptive Analysis of Pre-Test, Post-Test and Advanced Post Test Of Attitude Towards Science

Pre Test

Post Test

Advanced Post Test

134

Mean

26.2463

30.3881

30.3284

3.81417

1.68546

1.66239

Maximum

Minimum

Skewness

-0.688

0.067

-0.038

Kurtosis

0.744

-0.121

-0.197

The findings presented in Table 1 demonstrate a significant improvement in students’ attitudes toward science

following the implementation of the Raspberry Pi-based laboratory intervention. Attitudes were measured at

three stages: Pre-Test, Post-Test, and Advanced Post-Test. The mean score for the Pre-Test was 26.25 (N = 134,

SD = 3.81), indicating a moderate level of attitude towards science prior to the intervention. Following 12 weeks

of experiential learning using Raspberry Pi technology on the topic of Electricity, the PostTest mean score

increased notably to 30.39, with a reduced standard deviation of 1.69. This indicates not only a considerable

increase in the average attitude score but also greater consistency among students in their responses. The

Advanced Post-Test mean score remained high at 30.33 (SD = 1.66), suggesting the positive effect of the

intervention was sustained beyond the immediate learning period. The increase in mean score by 4.14 points

from the Pre-Test to the Post-Test can be interpreted as a strong indication of the effectiveness of the experiential

learning approach in enhancing students’ engagement and attitude toward science. Moreover, the minimum score

also showed a dramatic improvement—from 12 in the Pre-Test to 26 in both Post-Test and Advanced Post-Test.

This suggests that students who initially had a low attitude score toward science experienced substantial

improvement. The maximum scores remained consistently high across all three phases (35 in both the Pre-Test

and Post-Test, and 34 in the Advanced Post-Test), indicating that high-performing students maintained their

strong, positive attitudes throughout the study.

In terms of distribution, the skewness number went from -0.688 in the Pre-Test, which revealed a leftskewed

distribution (where more students had lower scores), to 0.067 in the Post-Test and -0.038 in the Advanced Post-

Test. This shows that the answers were more even and balanced after the intervention. This improvement means

that students' attitudes were more evenly spaced out, with fewer very low scores and more constant positive

views. The kurtosis values also changed. They moved from 0.744 in the Pre-Test to -0.121 in the Post-Test and

0.197 in the Advanced Post-Test. These statistics suggest that the distribution got flatter after the intervention.

This suggests that scores were less crowded around the mean and positive sentiments were more evenly spread

out. The analysis's numbers suggest that the Raspberry Pi-based lab learning had a large and enduring impact on

how pupils felt about science. The higher mean scores, lower standard deviation, better minimum scores and

more even score distribution all point to the fact that the intervention worked for a lot of different types of

learners. These results support the premise that STEM schooling that is hands-on and uses technology might

change how students think about science, especially in the years before college.The analysis of students' attitudes

towards mathematics, as one of the core components of STEM, reveals a notable and consistent upward trend

across the three phases of assessment: Pre-Test, Post-Test, and Advanced Post-Test following the implementation

of the Raspberry Pi-based laboratory learning intervention. During the Pre-Test phase, the mean score for attitude

towards mathematics was recorded at 23.47 (N = 134, SD = 3.18). This baseline indicates that students generally

held neutral to moderately low perceptions of mathematics prior to the intervention.

Moreover, the standard deviation of 3.18 suggests a fairly wide variation in students’ attitudes, implying

inconsistency in how mathematics was perceived among the cohort. Following the intervention, there was a

significant increase in the Post-Test mean score, rising to 29.25 (SD = 2.31). This marks an improvement of

approximately 5.78 points, indicating that students not only developed a more positive attitude toward

mathematics, but that the variation in their responses also decreased. The reduction in standard deviation from

3.18 to 2.31 suggests a more unified shift in the group towards favourable perceptions, reflecting the

effectiveness of experiential, hands-on and interdisciplinary learning in altering students’ mathematical outlook.

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 48

www.rsisinternational.org

Table 2. Descriptive Analysis of Pre-Test, Post-Test and Advanced Post Test Of Attitude Towards Mathematics

By the Advanced Post-Test phase, the mean score remained high at 29.01 (SD = 2.13). Although slightly lower

than the immediate post-intervention mean (by 0.24 points), this minimal decline still indicates a sustained

positive attitude. Notably, the standard deviation continued to decrease, highlighting greater consistency in

students’ positive views towards mathematics over time. The change in minimum scores is particularly

significant: from 13 in the Pre-Test to 23 in the Post-Test and 24 in the Advanced Post-Test. This demonstrates

a substantial uplift among students who previously had the weakest attitudes, reflecting the inclusive impact of

the intervention. The maximum score also increased, reaching 35 in both the Post-Test and Advanced Post-Test,

compared to 34 in the Pre-Test, indicating that even high-performing students benefited from the enriched

learning experience. In terms of distribution, the skewness and kurtosis values across all three phases are within

acceptable ranges (between -1 and +1), indicating that the data is approximately normally distributed and that

no extreme outliers have skewed the results.

Notably, the shift from slight negative skewness (-0.049) in the Pre-Test to positive skewness (0.072 and 0.171)

in the subsequent phases suggests that more students scored towards the higher end of the scale after the

intervention. Overall, the consistent rise in mean scores, reduction in variability and improvement in minimum

scores provide compelling evidence that the Raspberry Pi-based experiential learning model not only enhanced

students’ attitudes towards mathematics but also led to lasting improvements across the entire student cohort.

These findings underscore the value of integrating practical, STEM-oriented tools into conventional physics

instruction to promote interdisciplinary thinking and a more positive mathematical mindset. The descriptive

analysis of attitudes towards engineering and technology, as presented in Table 3, shows a significant shift in

students’ perceptions following the implementation of the Raspberry Pi-based Physics laboratory intervention.

This domain, which forms a crucial component of STEM education, was assessed across three key phases:

PreTest, Post-Test, and Advanced Post-Test. The data demonstrate an upward trend in students’ attitudes,

reflecting the impact of experiential learning and the integration of technology in laboratory instruction.

Table 3. Descriptive Analysis of Pre-Test, Post-Test and Post-Test of Attitudes Toward Technology and

Engineering

134

Min

24.1045

29.2015

28.9254

3.53982

2.08027

2.04324

Maximum

Minimum

Skewness

-0.655

0.154

0.199

Kurtosis

0.635

-0.224

0.041

In the Pre-Test phase, the mean score recorded was 24.10 (N = 134, SD = 3.54). This relatively modest mean

score indicates a moderate baseline attitude towards engineering and technology among pre-university students

prior to the intervention. The wide standard deviation of 3.54 at this stage suggests considerable variation in

students’ responses, highlighting that some students held negative or neutral views towards the relevance and

application of engineering and technology in their studies. However, a notable transformation occurred following

the 12-week intervention using Raspberry Pi. The Post-Test mean score rose significantly to 29.20, marking an

increase of over 5 points, which is a substantial gain in the context of attitudinal research. The standard deviation

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 49

www.rsisinternational.org

also dropped considerably to 2.08, indicating that students’ responses became more consistently positive. The

Advanced Post-Test results further confirmed the sustainability of this change, with a mean score of 28.93 (SD

= 2.04), showing only a minor decline of 0.27 points from the immediate post-test while maintaining a strong

overall improvement compared to the pre-intervention phase.

The minimum score improved markedly from 13 in the Pre-Test to 25 in both the Post-Test and the Advanced

Post-Test. This indicates that even students who initially had the lowest levels of interest or positive perception

towards engineering and technology experienced considerable attitudinal growth. Likewise, the maximum score

increased from 31 to a perfect score of 35 in the Post-Test. It remained consistent in the Advanced Post-Test,

suggesting that the highest-performing students maintained their enthusiasm and strong attitudes over time. The

distributional characteristics of the data also reveal meaningful shifts. The skewness value, which was -0.655 in

the Pre-Test, indicates that the initial distribution of scores was skewed to the left, suggesting that more students

had lower attitudes towards engineering and technology. After the intervention, skewness values improved to

0.154 in the Post-Test and 0.199 in the Advanced Post-Test, signifying a more balanced and symmetrical

distribution of attitudes. Similarly, the kurtosis value decreased from 0.635 (Pre) to 0.224 (Post) and 0.041

(Advanced Post), indicating a shift toward a more normal and evenly distributed distribution of scores.

Effectiveness on Attitudes towards STEM

These findings provide strong evidence of the effectiveness and sustainability of the Raspberry Pi-based

intervention in positively transforming students’ attitudes toward engineering and technology. The increase in

mean scores, the dramatic rise in minimum scores, the narrowing of score variability and the normalization of

distribution patterns all point to the intervention’s ability to engage students across a broad spectrum of ability

levels. More importantly, the results suggest that when students are exposed to real-world applications of

engineering through hands-on, inquiry-based tasks, they are more likely to develop an appreciation for the

relevance and importance of engineering and technology in both academic and everyday contexts.

Hence, the Raspberry Pi-based experiential learning module not only strengthened students’ conceptual

understanding of Electricity but also played a critical role in cultivating a more positive and enduring attitude

toward engineering and technology. This affirms the value of integrating STEM elements in a cohesive and

meaningful way within the pre-university curriculum to support the development of 21st-century skills and

STEM career aspirations. The inferential statistical analysis aims to measure the effectiveness of the Raspberry

Pi-assisted Electrical Laboratory Learning intervention on the research variable, which is the attitude toward

STEM. The MANOVA test with repeated measurements was used to test the hypotheses built to answer each

research question. Thus, a MANOVA test with repeated measurements at a significance level of p = 0.05 was

conducted to determine the main effect of test time on the dependent variables involved, namely attitude towards

science, attitude towards mathematics and attitude towards engineering and technology. Test time is categorized

as an internal variable (within variable) used. Based on the MANOVA test perspective with Repeated

Measurements (Hair, 2009), a research variable is considered an internal variable when it is measured repeatedly

within the same sample.

Table 4. Multivariate Test Results (MANOVA) for Mean Attitude Scores Towards STEM

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 50

www.rsisinternational.org

In the context of this study, test time refers to variables that are measured repeatedly against the study sample

specifically before the intervention (pre-questionnaire), immediately after the intervention (postquestionnaire

and after a specified period following the end of the intervention (extended post-questionnaire). Thus, the

purpose of testing the main effect of the internal variable, which is the test time, on the dependent variable is to

determine if there is a significant difference in the mean score of the questionnaire based on repeated

measurements, namely the pre-questionnaire, the post-questionnaire and the advanced postquestionnaire. Based

on inferential statistical analysis as well, the size of the effect caused by these internal variables can be expected

(Tabachnick & Fidell, 2007). The results of the multivariate test showed the main effect of test time on the

dependent variable based on a significant value of p<0.05. The results of Table 1.4 show a significant effect of

test time (p < 0.05). This indicates a significant difference between the pre, post and post-extended tests. Findings

also show a significant main effect on the attitude construct towards STEM. This indicates a difference in the

findings between the constructs of attitudes toward STEM, specifically attitudes toward science, mathematics,

engineering and technology. The significant interaction effect between test time and attitude construct towards

STEM leads to the conclusion that the mean score of attitudes towards STEM is influenced by the interaction

between test time and attitude construct towards STEM.

Table 5 shows the semi-partial eta squared value, η², which indicates the size of the effect, showing the relative

magnitude of the difference between the mean or the amount of variance in the dependent variable that can be

expected from knowing the independent variable (Tabachnick & Fidell, 2007). Cohen (1988) has proposed

guidelines for the value of eta squared, which are as follows: 0.01 = small, 0.06 = medium, and 0.14 = significant

effect. According to Tabachnick and Fidell (2007), the same guidelines can be used to predict effect sizes from

the semi-partial eta-squared values obtained. Therefore, the semi-partial eta squared value (η²) obtained in this

study indicates that the size of the test time effect on attitudes toward science, mathematics, engineering, and

technology is enormous. These results showed an improvement in attitudes towards science, mathematics,

engineering and technology after the twelve-week intervention ended. Therefore, it can be concluded that the

Raspberry Pi-based Electrical laboratory learning module has a significant effect on increasing positive attitudes

and advancing post-secondary education toward STEM among pre-university students.

Table 5. Effect of Raspberry Pi Intervention on Attitudes towards STEM

STEM

Component

Pre-Test

Mean

(SD)

Post-

Test

Mean

(SD)

Advanced

Post-Test

Mean

(SD)

Change &

Significance

Interpretation of Remarkable

Changes

Science

26.25

(3.81)

30.39

(1.69)

30.33

(1.66)

4.14-point increase,

Wilks’ Lambda =

0.205, p < .001, η² =

0.795

Large increase in mean score

and drop in SD indicate strong

improvement and consistency;

intervention highly effective.

Mathematics

23.47

(3.18)

29.25

(2.31)

29.01

(2.13)

5.78-point increase,

Wilks’ Lambda =

0.813, p < .001, η² =

0.638

Substantial mean gain and

reduced variability reflect

improved engagement with

mathematics through applied

STEM context.

Engineering

& Technology

24.10

(3.54)

29.20

(2.08)

28.93

(2.04)

5.10-point increase,

Wilks’ Lambda =

0.325, p < .001, η² =

0.795

Significant uplift in both low

and average scorers; sustained

positive perception of real-

world tech after intervention.

For mathematics attitudes, students showed enhanced engagement due to the analytical aspect of substantial

improvements in students’ attitudes toward the three core components of STEM, which are science, mathematics,

and technology and engineering. This intervention, designed around Experiential Learning Theory, emphasizes

hands-on, learner-centered experiences and has proven effective in transforming students’ perceptions and

engagement with STEM fields. Attitude toward science improved significantly after the twelveweek

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 51

www.rsisinternational.org

intervention. Students who previously showed low motivation in physics were more engaged when they had the

opportunity to interact with real data through electronic devices, observe live changes on the Raspberry Pi

interface and relate theory to observable phenomena. This hands-on approach addresses the limitations of

conventional chalk-and-talk physics lessons, which often fail to convey the dynamic nature of scientific inquiry.

Maison (2020) highlights that positive science attitudes stem from interactive and meaningful learning

environments where students build their understanding. Similarly, Oh and Yager (2004) emphasized that

students’ attitudes toward science improve in constructivist classrooms where active participation is central. In

the context of this study, students were not passive recipients of knowledge but rather active experimenters in

building circuits, observing outcomes and drawing conclusions. This hands-on approach circumvents the

constraints of traditional chalk-and-talk physics teachings, which frequently fail to communicate the dynamic

nature of scientific inquiry. Maison (2020) emphasizes that students' positive attitudes toward science are the

result of interactive and meaningful learning environments that facilitate the development of their

comprehension. In the same vein, Oh and Yager (2004) underscored that students' attitudes toward science are

enhanced in constructivist classrooms that prioritize active participation. Students were not passive recipients of

knowledge in the context of this study, they were active experimenters who constructed circuits, observed

outcomes and drew conclusions.

This experiential approach was instrumental in the correction of misconceptions and the cultivation of a more

profound appreciation for scientific inquiry. Additionally, there was a substantial improvement in the attitude

toward mathematics. The Raspberry Pi experiments contextualized mathematical reasoning, in contrast to

traditional settings where mathematics is taught abstractly. In order to generate graphs and interpret numerical

outputs, students were obligated to analyse voltage, resistance and current values in real-time. This increased the

accessibility and relevance of mathematics. Integrated STEM activities, particularly those that involve data

interpretation and engineering tasks, have been demonstrated to improve students' perception of mathematics as

a valuable tool rather than a rigid subject (Valko & Osadchyi, 2021). The active manipulation of variables and

observation of changes not only encouraged critical and analytical thinking but also enhanced mathematical

reasoning. Students' attitudes toward mathematics-related activities underwent a transformation as they

developed confidence in managing numerical tasks within meaningful scenarios, resulting in a decrease in

apprehension and an increase in enthusiasm. The most substantial improvements were observed in attitudes

toward technology and engineering. The Raspberry Pi, a microcomputer, provided students with an introduction

to the fundamental principles of computer engineering, sensor systems and programming areas that are typically

inaccessible in traditional physics laboratories. Students gained a sense of control over technological instruments

and technology was demystified as a result of this exposure. The utilization of microcomputers such as Raspberry

Pi in laboratories facilitates the integration of theoretical knowledge with real-world applications, thereby

enhancing students' understanding of engineering concepts, as per Hatta and Budi Yanto (2021). The students in

this study were involved in a variety of tasks, including the programming of GPIO pins, the connection of circuits

and the troubleshooting of their installations.These activities facilitated the development of a mindset of

innovation and problem-solving skills. Balon and Simić (2019) contend that the integration of Raspberry Pi into

physics education provides a cost-effective yet significant instrument for motivating students to pursue

technological and engineering careers. Students maintained their enhanced attitudes, as evidenced by the

Advanced Post-Test, which was administered four weeks following the intervention. This implies that the

influence of Raspberry Pi-based learning is not merely superficial or transient, but rather leads to enduring

cognitive and affective growth. The notion that authentic, context-rich learning environments foster long-term

engagement and motivation in STEM is substantiated by these findings (Eugenijus, 2023). Therefore, this

investigation provides evidence that Raspberry Pi is not only a cost-effective innovation but also a pedagogically

effective approach to laboratory learning.

CONCLUSION

The results of the study indicate that all of the study's objectives were satisfactorily accomplished, and that

laboratory learning can improve the performance of low-achieving students in both the classroom and their social

environments. In summary, this investigation illustrates the substantial improvement in students' STEM attitudes

that can be achieved by incorporating the Raspberry Pi into the Physics laboratory. Therefore, the results of the

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 52

www.rsisinternational.org

research were in accordance with a previous study that demonstrated that the use of Raspberry Pi in the physics

laboratory simplifies the understanding and retention of physics concepts (Suri, 2021; Pathoni, Alrizal, &

Febriyanti, 2020). The results of this study were in agreement with those of an earlier study, which determined

that Raspberry Pi can be used as an alternative medium for teaching physics in a laboratory setting and that its

use in a physics laboratory classroom can increase students' enthusiasm and engagement (Lin et al., 2015).

Furthermore, the integration of Raspberry Pi into the Physics laboratory can facilitate the development of

learners' visual representation and high-level thinking abilities (Haroky, 2019). The author suggests that

additional research be conducted to determine the impact of the Raspberry Pi on changes in visual representation

abilities and learning engagement in physics laboratory applications. The scope of this investigation can be

further expanded by incorporating additional study themes and issues from Physics and other STEM disciplines.

ACKNOWLEDGMENT

Full appreciation is given to the Ministry of Education Malaysia for the sponsorship of the "Hadiah Latihan

Persekutuan" (HLPS) and Universiti Pendidikan Sultan Idris (UPSI), which enabled the successful

implementation of this study.

REFERENCE

1. Ariza, M., & Baez, L. (2022). Integrating low-cost microcomputers in science education: Enhancing

students’ engagement and understanding. Journal of Science Education and Technology, 31(4), 512–524.

2. Bakar, R. (2022). Student attitudes towards science and technology: The impact of teacher-centred

approaches. Asian Journal of Education and Training, 8(1), 25–33.

3. Balon, N., & Simić, M. (2019). Raspberry Pi as an affordable tool for physics education laboratories.

Physics Education, 54(5), 055017.

4. Baran, E., Canbazoglu Bilici, S., Mesutoglu, C., & Ocak, C. (2019). Integrating STEM into preservice

science teacher education: A grounded theory study. International Journal of STEM Education, 6(1), 1–

21.

5. Beier, M. E., Kim, M. H., Saterbak, A., Leautaud, V., Bishnoi, S., & Gilberto, J. M. (2019). The effect of

authentic project-based learning on attitudes and career aspirations in STEM. Journal of Research in

Science Teaching, 56(1), 3–23.

6. Ceylan, E., & Ozdilek, Z. (2015). A comparative study on integrated STEM instruction and conventional

teaching in physics education. European Journal of Physics Education, 6(3), 1–13.

7. Chambers, S. K. (2014). Improving student motivation and attitudes towards physics. Science Education

International, 25(2), 102–116.

8. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.

9. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd

ed.). SAGE Publications.

10. Dewey, J. (1938). Experience and education. Macmillan.

11. Eugenijus, V. (2023). Interactive STEM integration for enhancing learning engagement: A review of

recent evidence. Contemporary Educational Research Journal, 11(2), 101–117.

12. Faridi, A., Ahmad, N., & Rahman, R. (2021). Active learning and conceptual understanding in science

classrooms: A systematic review. International Journal of Instruction, 14(4), 213–234.

13. Forbes, A., & Skamp, K. (2015). Secondary students and engagement with science: What are the

implications for science teachers? Teaching Science, 61(1), 6–15.

14. Fullan, M., & Langworthy, M. (2013). Towards a new end: New pedagogies for deep learning. Pearson

Education.

15. Hacieminoglu, E. (2016). Elementary school students’ attitudes toward science and related variables.

16. International Journal of Environmental and Science Education, 11(2), 35–52.

17. Hair, J. F. (2009). Multivariate data analysis (7th ed.). Pearson.

18. Haroky, A. (2019). Enhancing students’ visualization skills in physics through microcomputer-based

learning. International Journal of Education in Mathematics, Science and Technology, 7(4), 315–326.

19. Hatta, M., & Budiyanto, M. (2021). Microcomputer-assisted physics experiments: Bridging theory and

practice. Journal of Physics: Conference Series, 1805, 012012.

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)

ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVII November 2025 | Special Issue

Page 53

www.rsisinternational.org

20. Hoehn, J. R., Hernandez, P. R., & Koretsky, M. D. (2021). Barriers to implementing open-ended practices

in undergraduate STEM laboratories. Journal of Engineering Education, 110(2), 311–333.

21. Idris, M., & Idris, S. (2020). The role of practical learning in improving 21st-century skills among

students. International Journal of Learning, Teaching and Educational Research, 19(6), 202–215.

22. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice

Hall.

23. Kuo Hung Tseng, K. H. (2011). Students’ attitudes toward STEM: The mediating role of motivation.

Research in Science Education, 41(5), 793–813.

24. Lin, C. H., Yen, C. H., & Chang, W. C. (2015). Exploring Raspberry Pi-based physics experiments in

high school education. International Journal of Online and Biomedical Engineering, 11(6), 45–50.

25. Maison, M. (2020). Students’ attitudes toward science learning: The influence of experiential learning.

Journal of Physics: Conference Series, 1521, 042043.

26. Makhrus, M., Wahyudi, W., & Zuhdi, M. (2021). Teacher-centered instruction and misconceptions in

physics learning. Jurnal Pendidikan Fisika Indonesia, 17(1), 37–48.

27. Mahmood, S., Shah, A., & Ahmad, M. (2019). Microcomputers in laboratory learning: Opportunities and

challenges. Education and Information Technologies, 24(5), 3313–3327.

28. Mpofu, N. (2019). Bridging the gap between theory and practice in STEM education. African Journal of

Research in Mathematics, Science and Technology Education, 23(3), 275–287.

29. Naukkarinen, J., & Bairoh, S. (2020). Integration of physics with engineering contexts in secondary

education. Physics Education, 55(5), 055012.

30. Oh, P. S., & Yager, R. E. (2004). Development of positive attitudes toward science through constructivist

teaching. International Journal of Science Education, 26(8), 903–918.

31. Pathoni, M., Alrizal, A., & Febriyanti, D. (2020). The use of Raspberry Pi in physics laboratory learning

to improve students’ understanding. Jurnal Pendidikan Sains Indonesia, 8(2), 101–109.

32. Prasetya, A., Hirashima, T., & Hayashi, Y. (2020). Students’ preferences for open-ended experimental

tasks in science learning. International Journal of Science Education, 42(9), 1421–1440.

33. Purzer, S., Goldstein, M. H., Adams, R. S., Xie, C., & Nourian, S. (2015). An exploratory study of

engineering design as a contextual learning approach for STEM integration. Journal of Pre-College

Engineering Education Research, 5(2), 40–53.

34. Rasdi, N. M., Hassan, N., & Mahmud, M. (2021). Evaluating intervention effectiveness using

quasiexperimental design. Malaysian Journal of Learning and Instruction, 18(1), 175–192.

35. Ravitz, J. (2010). Beyond changing culture in small high schools: Reform models and changing

instruction with project-based learning. Peabody Journal of Education, 85(3), 290–312.

36. Spaan, D., Kolloffel, B., & de Jong, T. (2022). The role of active learning in developing conceptual

understanding in physics. Learning and Instruction, 78, 101505.

37. Suri, R. (2021). Simplifying physics concepts through low-cost microcomputers. Journal of Science

Education Research, 12(3), 215–224.

38. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Pearson Education.

39. Valko, N., & Osadchyi, V. (2021). Integrated STEM learning through collaborative projects in physics

education. European Journal of STEM Education, 6(1), 1–12.

40. Voo, L. P., Hemani, A., & Cassidy, P. (2022). Electricity concepts in physics: Bridging theory and

realworld applications. Physics Education Research Journal, 18(2), 55–64.

41. Wang, M. T., & Degol, J. (2013). Motivational pathways to STEM career choices: Using expectancy-

value theory. Journal of Educational Psychology, 105(2), 249–263.

42. White, R., & Harrison, A. (2012). The impact of experiential learning on science attitudes and

engagement. Research in Science Education, 42(2), 287–302.

43. Unfried, A., Faber, M., Stanhope, D. S., & Wiebe, E. (2015). The development and validation of a

measure of student attitudes toward science, technology, engineering, and math (S-STEM). Journal of

Psychoeducational Assessment, 33(7), 622–639.