Effect of computer simulation and animation-integrated instruction on pre-service science teacher trainees conceptual understanding and retention of acid-base chemistry and stoichiometry


Eshetu Desalegn Alemneh1* , Dereje Andargie Kidanmariam2 ,
Solomon Melesse Mengistie3 , Belete Bedemo Beyene4

1DEd Candidate in Chemistry Education, at Bahir Dar University (Ethiopia)

2Asso. Professor in Chemistry Education at Debre Berhan University (Ethiopia)

3Professor in Curriculum and Instruction at College of Education, Bahir Dar University (Ethiopia)

4Asso. Professor in Organic Chemistry at College of Science, Bahir Dar University (Ethiopia)

Received September 2023

Accepted November 2023


The study aimed to investigate the effect of computer simulation and animation-integrated instruction on pre-service science teacher trainees’ conceptual understanding and retention of acid-base chemistry and stoichiometry. A quantitative approach with a pretest–posttest-delayed test quasi-experimental design was used. In the study area, there were only two sections of first-year trainees in the natural science department. So a comprehensive sampling technique of the two intact sections was employed. The two intact classes were randomly assigned to an intervention group (IG) and a comparison group (CG). Data was collected using Acid-Base Chemistry and Stoichiometry Conceptual Understanding of a two-tier multiple-choice Test (ABSCUT). Parametric statistics (independent sample t-test and ANCOVA) were used for the data analysis. The independent sample t-test was used for the pre-test analysis to examine the prerequisite experiences of trainees in the two groups and male and female trainees in the IG before the intervention. The result showed no significant difference between the mean score of the CG and IG. The result also showed no significant difference in the mean score of male and female trainees in the IG. The ANCOVA was used for post-test and delayed test analysis after the intervention. The result indicated that there was a statistically significant difference between the two groups on conceptual understanding, F(1,49)=5.07, p=.029, partial eta squared=0.094, in favor of IG. This tends to imply the concepts of the trainees who received the intervention outperformed the comparison group. The ANCOVA result also indicated that gender difference has no statistically significant difference in the IG, F(1,24)=3.68, p=.067. The delayed-test analysis showed that the IG has higher retention than the CG. Based on the results, this study recommended that policymakers, chemistry curriculum experts, chemistry curricular material developers, and practitioners alike consider the application of computer simulation-integrated chemistry instruction to enhance learners’ conceptual understanding and retention.

Keywords – Conceptual understanding, Retention, Simulation, Animation.

To cite this article:

Alemneh, E. D., Kidanmariam, D. A., Mengistie, S. M., & Beyene, B. B. (2024). Effect of computer simulation and animation-integrated instruction on pre-service science teacher trainees conceptual understanding and retention of acid-base chemistry and stoichiometry. Journal of Technology and Science Education, 14(2), 453-472. https://doi.org/10.3926/jotse.2435

    1. 1. Introduction

Nowadays, chemistry education has been developing worldwide and becoming widely recognized as a research field (Taber, 2017). As a result, the use of effective chemistry instruction is the call of the day to better understand chemical concepts (Erduran & Scerri, 2003). The emphasis on the philosophy of chemistry education epistemologically underpins the knowledge of chemistry and has the potential to re‑energize the importance of models and representations during the instructional process (Treagust, Chittleborough & Mamiala, 2002). A model-based representation in chemistry instruction can contribute to meaningful learning engagement and enhance conceptual understanding. As many chemistry concepts are complex and difficult to conceptualize, learners face challenges in constructing knowledge and achieving meaningful learning (Ali, 2012). To minimize the abstract nature and enhance meaningful chemistry learning, there is a need to integrate chemistry instruction with the three levels of representation (Treagust & Chandrasegaran, 2009). Macroscopic, submicroscopic, and symbolic levels are the three levels of representation (Hadinugrahaningsih, Rahmawati & Ridwan, 2017; Johnstone, 1991; Tang & Abraham, 2016).

Learning chemistry at the submicroscopic level often requires the aid of models and images, which are used to enhance the conceptual understanding and retention of the learners (Maehr & Meyer, 1997; Treagust, Chittleborough & Mamiala, 2003). Chemists developed the concept of mental visualization of submicroscopic molecules and the changes associated with them. Through this, mental representations can be expressed symbolically using equations, tangible models, graphs, and drawings (Al-Balushi & Al‑Hajri, 2014; Kozma & Russell, 2005). Learners usually perceive the macroscopic phenomena, but they lack concentration on the basic building block of chemical concepts-the submicroscopic phenomena (Williamson, 2011; Williamson & Abraham, 1995). Moreover, studies indicate that superficial experiences of learners of the submicroscopic level of representation lead learners to miscomprehend the relationship that exists among the triplet levels of representing phenomena (Johnstone, 1993; Treagust & Chandrasegaran, 2009). Consequently, learners fail to link visual and conceptual representations, and they usually face misconceptions and learning difficulties about chemical concepts due to their abstract nature (Al-Balushi & Al-Hajri, 2014; Özmen, Demircioğlu & Coll, 2009; Susilaningsih, Fatimah & Nuswowati, 2019).

The abstract concepts of chemistry require a variety of learning strategies to enhance learners’ conceptual understanding and minimize learning difficulties on different topics of general chemistry courses (Fensham, 1988; Hilton & Nichols, 2011; Kamisah & Nur, 2013; Sirhan, 2007; Taber, 2002; Zoller, 1990). Acid-base chemistry and stoichiometry are among the different contents usually incorporated into the general chemistry course that can be taught at the college level and have an application to everyday life. These topics are interrelated to each other and have several advantages for the knowledge and understanding of advanced chemistry courses. Although acid-base chemistry and stoichiometry have many advantages, they have some learning difficulties that hinder learners’ conceptual understanding and cause difficulty in solving problems (Anderson, 2020; Hand, Yang & Bruxvoort, 2007; Kousathana, Demerouti & Tsaparlis, 2005; Ross & Munby, 1991).

Different scholars investigated learning difficulties in different concepts of acid-base chemistry and stoichiometry. For example, Alvarado, Garritz and Mellado (2015) indicated that learners could not differentiate the degree of acidity of different solutions with the same concentration. Similarly, Demircioglu, Ayas and Demircioglu (2005) and Hoe and Subramaniam (2016) showed that learners could incorrectly correlate chemical structures with acidity or basicity and attempt to explain them based on the presence of H and OH. Elham and Dilmaghani (2019) disclosed that learners believed that temperature does not affect the dissociation system of acidic or basic solution and assumed that pure water’s pH is always seven. Other scholars, such as Kousathana et al. (2005) and Mubarokah, Mulyani and Indriyanti (2018), indicated that learners usually perceive a neutral solution as a solution that has pH=7. In pH calculations, learners usually assume that [H3O+] is only just from the dissociation of the acid. They thought that a solution of 10-8 M HCl had a pH value of 8. Other studies, (e.g. Rohmah & Virtayanti, 2021; Sheppard, 2006) indicated that learners do not generally understand that pH is a measure of concentration rather than a measure of strength. Other scholars indicate the existence of learning difficulties on the topics of stoichiometry (Huddle & Pillay, 1996; Schmidt, 1990). The idea of stoichiometry is not only challenging for learners but also it is a prerequisite to learning about other topics in general chemistry, including acid-base reactions (Evans, Yaron & Leinhardt, 2008; Gupta, 2019; Hand et al., 2007). To alleviate these and other similar epistemological problems, therefore, scholars suggest different alternative instructional strategies that enhance learners’ conceptual understanding and retention capacity at both symbolic and submicroscopic levels (Kozma & Russell, 2005; Treagust & Chandrasegaran, 2009).

Some studies suggest applying computer simulation and animation-integrated instruction to ease learners’ conceptual and multilevel understanding of chemistry. Today’s computer technology provides graphical representations in the form of animations and simulations that help learners relate their prior experience to scientific concepts and construct their mental models of chemical phenomena and theories (Liu, 2005). Animated images can improve students’ perception, cognitive thinking levels, understanding, and attention by altering their mental ideas into concrete images and relating basic science concepts to real-life experiences (Akçay, Feyzioğlu & Tüysüz, 2003; Sanger & Greenbowe, 2000). These reports suggested that conventional method integrating with simulation and animation(CMISA) can help learners to concretize abstract concepts by explaining the submicroscopic phenomena from macroscopic phenomena (Engida, 2017). According to studies, integrating technology into chemistry instruction has the potential to provide a multisensory stimulus and enhance learners’ conceptual understanding of chemical concepts at all levels of representation (Barnea & Dori, 1996; Wilujeng, Tadeko & Dwandaru, 2020). Applying computer simulations and animations for abstract topics provides an opportunity for learners to construct meanings and understand difficult concepts more easily by creating an interactive learning environment and enhancing retention (Mihindo, Wachanga & Anditi, 2017; Nduudee & Arokoyu, 2021; Sung & Ou, 2002). Scholars investigated the effect of technology on students’ retention capacity in chemistry learning and indicated that students who taught chemistry through technology-based instruction showed better retention than those taught through traditional methods (Hussain, Suleman, Din & Shafique, 2017; Rastegarpour & Badeleh, 2012). Proper utilization and application of simulation and animation can generally increase the quality of learning by allowing learners to express their real reactions (Suits & Srisawasdi, 2013). It can also create the opportunity to compress experiments at the classroom levels, dynamically present micro-mechanisms, enrich the learning methods by strengthening the connection between experiments and theories, and stimulate motivation for learning (Belletti, Borromei & Ingletto, 2006). Simulation allows learners to view and interact with models of phenomena and facilitate understanding phenomenal processes at the molecular level (Plass, Milne, Homer, Schwartz, Hayward, Jordan et al., 2012; Stieff, 2011).

There are conflicting reports on the effect of simulation and animation-based chemistry instruction on students’ conceptual understanding of differences by gender. For instance, Mihindo et al. (2017), Nkemakolam, Chinelo and Jane (2018), Poripo (2008), Sentongo, Kyakulaga and Kibirige (2013), and Ezeudu and Ezinwanne (2013) reported that simulation-based chemistry instruction does not show a significant difference between male and female students’ learning. Likewise, other researchers found that male and female students performed equally well in chemistry using computer-based instructional packages (Adesoji & Babatunde, 2005; Gambari, 2004). On the other hand, Chen and Howard (2010) indicated that male students show more positive motivation and learning towards simulation-based chemistry instruction. Similarly, Nduudee and Arokoyu (2021) researched the chemistry performance of gender differential effects of secondary school students in simulation-based instruction and found that the instruction caused differences, in favor of male students.

Eventhough a large number of studies indicated that computer simulation and animation enhance learners’ conceptual understanding and retention; some studies do not support the use of simulation and animation to enhance learning. For example, Jong (2010) and Kock (2018) cited in Krüger, Höfer, Wahl, Knickmeier and Parchmann (2022) reported that computer simulation causes cognitive and metacognitive difficulties in students’ learning. Similarly, Winberg (2006) indicated that the use of simulation as an instruction creates multimodal representation, causes split attention, and increases cognitive load on learners. The cognitive load theory claims that meaningful learning can only occur when the cognitive capacities of learners’ working memory cannot be overburdened (van Merriënboer & Sweller, 2005). Similarly, Hattie (2012) cited in Krüger et al. (2022) reported that computer simulation has low effects on the learning process (d=0.33). Another study by Sanger and Greenbowe (2000), indicated that college learners did not need visual aids like computer simulation in their teaching-learning process. This is because; the learners are mature enough to visualize mentally the chemical process at a submicroscopic level.

In addition, Kirschner (2002) indicated that visual representations for instruction can burden the limited learners’ working memory by imposing high intrinsic loads that affect conceptual understanding. Other scholars (e.g. Tversky, Morrison and Betrancourt (2002), indicated that animation-integrated instruction may not provide benefits over static graphics because animations are often complex, transitory, and fast‑paced which increases the cognitive load in the learners’ mind, causing difficulty in understanding the instruction. Scholars like Schnotz and Grzondziel (1996) and Mayer, Heiser, and Lonn (2001) indicated that learners who used animation achieved lower results in content questions and conceptual understandings, and caused learning impediments than static images.

As indicated, even though, most scholars agree that computer simulation and animation-integrated instruction enhances learning, some findings that do not support learning enhancement of computer simulations and animations. Therefore, there exists a lack of conclusiveness about the effect of simulation and animation-integrated instruction. In addition to this, most of the research was done mostly at the middle school and secondary school and rarely at primary school levels. To my knowledge, there are scarcities of such kinds of research among college pre-service teacher trainees, especially in the Ethiopian context. Therefore, this study intended to investigate the effect of computer simulation and animation‑integrated chemistry instruction on pre-service science teacher trainees’ conceptual understanding and retention. To this end, the study was designed to provide an authentic answer to the following research questions:

  1. 1.Do computer simulation and animation-integrated instruction affect learners’ conceptual understanding of chemical concepts in acid-base chemistry and stoichiometry? 

  2. 2.Do computer simulation and animation-integrated instructions cause gender differential effects on male and female learners’ conceptual understanding of acid-base chemistry and stoichiometry? 

  3. 3.Do computer simulation and animation-based instruction enhance learners’ retention of chemical concepts in acid-base chemistry and stoichiometry? 

  1. 2. Methodology

2.1. Research Method and Design

In this study, a quantitative research approach with a non-equivalent pretest-posttest-delayed test control group quasi-experimental design was employed. The quantitative research method was chosen as it helps to reduce prejudice, and the findings were presented in numerical formats that were mostly free of subjectivity. The study used a quasi-experimental design because the research participants were not assigned randomly into groups. After all, the researchers did not have the chance to form artificial groups. So naturally existing (intact) classes were used for the investigation technique(Creswell, 2014).

This study was conducted at Woldia College of Teachers Education (WCTE), Amhara Regional State, Ethiopia. It was conducted on pre-service science teacher trainees because the trainees are expected to be primary and middle school science teachers, which will have a great impact on the foundation of science education in general and chemistry education in particular. Moreover, the principal researcher could easily get permission from the college authorities and collaboration from the chemistry instructors to carry out the intervention. This collaboration could enhance and enrich the data by minimizing research administration constraints. In the college, there were 62 pre-service natural science teacher trainees in two sections (31:31) at the beginning of the 2022/2023 academic year. However, ten students were moved to Ethiopian Universities for remedial program, and 52 (27:25) trainees left at the college. The study used all the 52 trainees in the two sections using a comprehensive sampling technique and these two intact classes were randomly assigned to IG and CG. The diagram at Figure 1 indicated that the main sequential stages undertake in the research design.


Figure 1. Research Design Flow Chart

2.2. Research Procedures

Before implementing the intervention, the college officials and the participant pre-service science teacher trainees signed the informed consent. The researcher adjusts a classroom having computers for IG by using the goodwill of the college dean and the department head. The researcher gave training to the course instructor about how simulation and animation can be integrated into the gapped lecture and cooperative lecturing method. The pretest was given to gather information about the conceptual understanding of the trainees before the intervention. An independent sample t-test was run to analyze this pre-test score and the result showed that there was no statistically significant difference in the mean score of the CG( M=22.96, SD=6.52) and IG (M=21.07, SD=6.71); t(50)= -1.03, p = .31. This result showed that the IG and CG have similar pre-existing conceptual understandings about the general chemistry.

The two groups were taught acid-base chemistry and stoichiometry in a series of lessons. The topics covered during the instruction included in the acid-base chemistry and stoichiometry parts of the general chemistry course were; the nature and properties of acids and bases, dissociation of acids and bases, ionization constants of acids and bases, autoionization of water, hydrolysis of salts, methods of calculating pH and pOH, buffer solution, and quantitative relationship in chemical reactions(determining limiting reactants, excess reactants, theoretical yields, actual yields, and percentage yield). The comparison group was taught the selected topics through the conventional (cooperative and gapped lecture) methods alone, while the intervention group was taught the same topics with conventional methods integrated with computer simulation and animation, CMISA, which creates interactive lecture demonstrations. This means that the instructor used cooperative and gapped lecture pedagogy for both groups but employed computer simulation and animation-integrated approach for the IG. Fortunately, the two groups were taught the course by one instructor. The intervention stays for seven weeks, three hours per week, and the instructor prepared two types of lesson plans that showed the conventional approach and integration of simulation and animation into the conventional classroom.

Conventional method: In this method, the instructor taught the selected contents to the trainees in the comparison group through gapped lectures and cooperative instructional methods. Most instructors in the college usually use these two pedagogical methods.

Conventional method integrated with simulation and animation (CMISA): the instructor taught the selected contents to the trainees in the IG through the conventional method–integrated with simulation and animation that creates an interactive lecture demonstration. Samples of simulation and animation used during the instruction were given in Figure 2.

The simulation in Figure 2a showed that the pH of the acidic solution on the left side is 1.99 whereas the pH of the acidic solution on the right side is 4.50. The two solutions have similar concentrations but differ in strength, which indicates that pH is a measure of strength rather than concentration. Similarly, Figure 2b indicates that the pH of a certain solution can be negative or positive depending on the concentration. On the left side of the workbench, the pH meter indicates the pH of 10MHCl is -1.00 whereas the right side workbench contains 10M NaOH and the pH meter indicates (reads) a pH value of 15.00. This concept widen the idea of the trainees bounded that pH runs from 0 to 14.

Figure 2a. Simulation that Shows pH is a Measure of Concentration but not Strength
(Downloaded from http://phet.colorado.edu)

Figure2b. Simulation that Show pH can be Positive or Negative (Snapshot from Vlab Animation Software)