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Article

The Effect of Augmented Reality on Learning Meiosis via Guided Inquiry and Pecha Kucha: A Quasi-Experimental Design

by
António Faria
* and
Guilhermina Lobato Miranda
UIDEF, Instituto de Educação, Universidade de Lisboa, 1649-013 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
Information 2024, 15(9), 566; https://doi.org/10.3390/info15090566
Submission received: 14 August 2024 / Revised: 3 September 2024 / Accepted: 11 September 2024 / Published: 13 September 2024
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Abstract

:
This study investigates the effectiveness of using augmented reality (AR), combined with guided inquiry and the Pecha Kucha technique, on students’ academic outcomes when learning meiosis. The main objective was to analyse whether this combination presents significant differences in the academic performance of students in the experimental group (EG) compared to the control group (CG), who did not use AR. The research employed a quasi-experimental design involving three 11th-grade classes from a secondary school in Lisbon. Knowledge tests were administered post-intervention and at follow-up to assess the impact. To ensure the normality of the distributions, a Shapiro–Wilk test was applied and, to guarantee the homogeneity of variances, a Levene test was utilised. Independent and paired sample t-tests were performed. The results indicated that the innovative approach, combining AR with guided inquiry and Pecha Kucha, enhanced student engagement and led to improved academic performance. The study highlights the importance of teacher support during guided inquiry, showing that proper guidance maximises learning outcomes. Findings suggest that integrating active methodologies and current technologies can enrich Biology teaching and improve understanding of complex concepts like meiosis. This research contributes to existing literature by demonstrating the potential of AR, guided inquiry, and the Pecha Kucha technique in enhancing educational outcomes.

1. Introduction

Augmented reality (AR) is characterised as a three-dimensional simulation environment created through software and hardware to provide the user with the most realistic interactive experience possible [1]. This concept is also understood as encompassing all situations where the real world is supplemented with the presentation of virtual images (through computer graphics), allowing interaction [2]. Initially defined through the virtuality continuum [3], AR is now defined within a broader framework by including various realities [4]. AR is, therefore, a system that combines: (i) real and virtual objects, (ii) real-time interaction, and (iii) a three-dimensional combination of real and virtual elements [5]. The use of AR in learning contexts related to Biology, Science, or STEM areas is seen as enhancing students’ academic performance [6,7,8]. Technologies that enable AR, such as current mobile phones and other portable devices, favour its integration into school learning contexts [9,10]. These technologies are also important in learning non-visible concepts [11] or those that are difficult to understand, such as those related to genetics, as mechanical learning leads to failure and only proper instruction allows students to achieve meaningful learning [12]. Teaching sciences using the Inquiry Principle is considered to promote the development of skills such as communication, collaboration, reflection, and creativity [13]. Its five phases—orientation, conceptualisation, investigation, conclusion, and discussion [14]—can be organised in a cyclical vision or fluid paths in the development of work activity [15]; however, they require guidance or support from the teacher to be effective in student learning [13,15,16]. Pecha Kucha is a presentation methodology created in 2003 in Japan by architects Mark Dytham and Astrid Klein [17,18,19]. This presentation format can be based on PowerPoint, where 20 slides run automatically, each lasting 20 s [17,18,19,20]. This research was innovative in the school where it was conducted, due to the mandatory use of Pecha Kucha in the discussion phase of guided inquiry and also due to the integration of AR. The influence on students’ learning was quantified through the evaluation of a written test, conducted at two points separated by fifteen days, a post-test, and a follow-up.
Recent literature reviews highlight AR as promoting more meaningful learning with higher achievements and motivation. [21] but also reinforcing in-depth understanding as it provides the 3D visualisation of objects [22]. The need for more studies to evaluate the effect of AR combined with different teaching strategies has also been highlighted [22,23]. Therefore, in this study, we have meticulously structured our research to provide novel and substantial data by integrating the guided inquiry teaching strategy with the Pecha Kucha presentation format, further increasing with augmented reality (in the experimental group). This approach aims to explore the synergistic effects of these methodologies in enhancing educational outcomes.
The research problem of this study was formulated as a question as follows: Does the use of an AR app associated with the guided inquiry teaching strategy and the Pecha Kucha technique have positive effects on students’ academic performance concerning meiosis learning?
This problem was broken down into the following research questions:
Q1—Does the association of AR with guided inquiry produce better academic performance in the post-test of students in the experimental group compared to the control group?
Q2—Are there differences in academic performance in the follow-up test of students in the experimental group compared to the control group when AR is integrated with guided inquiry in meiosis learning?
Q3—Are there significant differences between the post-test and the follow-up test in the EG students’ meiosis learning using guided inquiry associated with AR?
Q4—Are there significant differences between the post-test and follow-up test results in the CG students’ meiosis learning using guided inquiry without AR?
This paper is structured as follows: we begin with an introduction that succinctly presents inquiry-based learning and guided inquiry as the implemented educational strategy, Pecha Kucha for the presentation moment, and augmented reality, along with the application utilised in this study. Section 2 delineates the materials and methods, with a particular focus on the quasi-experimental design employed in our research. In Section 3, we present and analyse the empirical results obtained. Section 4 is dedicated to the discussion of these results, addressing the proposed research questions. Finally, Section 5 provides the conclusion.

1.1. Inquiry-Based Learning and Guided Inquiry

Inquiry-based learning is an educational strategy that allows students to establish a connection between their knowledge and new scientific learnings [24] and is also seen as a learning process similar to that developed by scientists [25]. This strategy is considered very suitable for science teaching and promotes critical thinking in students [26], providing cognitive benefits as they are encouraged to ask questions, investigate, and build their own understanding of concepts [14]. In a literature review of 32 articles on inquiry-based learning in an educational context [15], the authors proposed an organisation of the phases of inquiry-based learning based on a broad framework of concepts collected from the studies. Thus, they organised the inquiry process, involving five phases: orientation (introduction to the topic); conceptualisation (questions, hypothesis formulation); investigation (planning, gathering information from various sources, interpretation and analysis); conclusion (final product, problem-solving); discussion (presentation or communication of the process results). In this strategy, students communicate their conclusions, which are debated with peers and serve as a stimulus for learning, as they have investigated scientifically oriented questions. In the process of evaluating the acquired knowledge, these authors consider it appropriate to compare it with previous knowledge for better reflection on new problem-solving actions. These phases can constitute a cycle that leads to the repetition of moments and, although the authors consider various paths, all start with the orientation phase [15]. In an analysis of 15 studies [14], the authors evaluated the integration of AR in the inquiry-based learning strategy, mentioning that the authors analysed cognitive aspects, verifying advantages in its use compared to groups that did not use it through better academic performance. Some studies indicate other aspects that improved, including those related to motivation such as attention, interest, and engagement.
The guided discovery [16] or guided inquiry [13] perspective is based on the phases of inquiry-based learning but explicitly states the importance of providing students with structured support: “How much guidance is just right depends on student’s knowledge and skills, which in turn vary across the different phases of the inquiry cycle and gradually increase during the learning process”. [16] (p. 382); “To be successful, inquiry learning needs to be combined with guidance. This guidance has two aspects, preparing students for inquiry with the right level of prior knowledge and providing guidance during the inquiry activities themselves”. [13] (p. 398). This support is presented in several studies with clear evidence of improved learning [25,26,27]. Taking these considerations into account, we determined that the guided inquiry approach was the most appropriate teaching strategy to optimise students’ performance in this learning process. This decision was based on the premises that students were engaging with the intricacies of meiosis as a cell division process for the first time, as the inquiry learning model encourages students to actively discover concepts and knowledge independently, fostering concrete thinking aligned with the nature of science, and epitomises 21st-century learning by integrating a scientific approach with real-world problems, thereby making learning more relevant and impactful for students [28,29].

1.2. Pecha Kucha

The Pecha Kucha presentation format was created in Japan and has gained great popularity in various fields, including education [18]. The highly visual approach consists of 20 slides, each displayed for 20 s, with automatic transition, making the overall presentation a total of 6 min and 40 s. This format is considered advantageous when the topics studied require greater attention, given the concise visual nature that promotes student interest [30,31]. In the context of higher education, the importance of using Pecha Kucha has been considered, resulting in better quality presentations, both in clarity and student engagement, as well as also favouring the presenter’s communication [32]. Another notable aspect is the time constraint, which leads to the choice of effective, organised, and well-integrated images within the content [17,20]. Given the maximum presentation time, it is an advantageous format for use in large classes [20]. Pecha Kucha can also be used as a form of formative assessment by allowing quick feedback to students on their presentations and communication skills [33]. Despite using a high number of slides, Pecha Kucha is a quick, visually appealing presentation that facilitates attention to the presenter’s speech [34]. Its construction in PowerPoint is facilitated by using the “Transitions” tab option, setting the “Duration” to 20 s, followed by “Apply to all”, or, alternatively, by using the following website: https://www.pechakucha.com/pkcreate (accessed on 4 August 2024) (registration required). In a study about Pecha Kucha presentations [35], the authors highlighted eight key advantages. Firstly, these presentations are well-organised. Secondly, Pecha Kucha motivates students to practice more. Thirdly, the information presented is clear and concise due to the time constraints. Additionally, the audience remains attentive to the 20-s slide rule. The slides are visually appealing, featuring minimal text and more images. This method helps students focus on key points, avoiding off-topic discussions. Furthermore, Pecha Kucha encourages discussions after the presentation. Lastly, presenting in this format helps students improve their overall presentation skills.

1.3. AR and AR Application

Since Sutherland’s initial concepts in the 1960s [4], AR has significantly evolved to its current applications, including teaching and learning. The advantages of AR in the classroom are numerous: it improves students’ understanding and retention of more difficult knowledge, creates motivation and greater engagement, and promotes teamwork and academic success. These benefits are highlighted in several studies [6,10,36], which demonstrates that AR is a pedagogical ally that transforms the classroom into a dynamic and enriching environment, in addition to being a very current technological tool. The advantages of AR increase when combined with appropriate teaching strategies, such as inquiry-based learning [14]. The result is an educational ecosystem in which students actively participate, promoting an improvement in the development of skills such as collaboration, negotiation and the debate of ideas, synthesis, analysis, and critical reflection. AR can be triggered without a marker (through images or real objects), using a marker (QR code), or by location (GPS).
Augmented reality (AR), as an integrated technology in educational contexts, offers significant added value both in learning and in association with learning strategies [9]. Its integration into classroom activities is facilitated by the easy access to current mobile devices [37,38] and the vast number of available AR applications [39]. Among the various advantages of using AR in learning contexts is the visuospatial process [38]; improved learning performance [11,40,41]; enhanced collaboration [9], which supports problem-solving [42]; and the promotion of inclusion, autonomy, and skill development [43]. Additionally, AR enables the teaching of inaccessible or invisible aspects, the simulation of dangerous experiences, and the inclusion of abstract concepts [7,8,44,45], as well as interaction with three-dimensional models that enhance acquisition and comprehension [46]. In Biology, AR supports the representation of aspects at various scales, facilitating macro, micro, and symbolic learning [11].
The app División meiótica 3D was created by the Laboratory of Research and Technological Innovation for Science Teaching at the University of La Serena (LIITEC-ULS)-https://liitec.userena.cl/rte/meiosis-3d/ (accessed on 4 August 2024) and can be downloaded for free for iOS and Android systems. AR is triggered by markers available in a planning guide, which can be downloaded in Spanish, English, or Portuguese. The scientific rigour is high, and the generated images include a detailed explanation of each moment of the meiotic division process. The meiotic phases involving chromosome movement, such as anaphase I, where the polar ascent of homologous chromosomes occurs, or anaphase II, where the polar ascent of chromatids occurs, are represented in an animated way, facilitating the spatial visualisation of this phenomenon. Therefore, we consider this app to be an important tool as it allows students to visualise meiosis aspects that are not visible in school laboratory class, due to their microscopic nature. Additionally, it presents dynamic aspects that are not observable in meiosis-prepared microscope slides (due to fixed and preserved material).
To conclude, we consider that the integration of AR within educational settings, in recent years, has demonstrated significant potential in enhancing student engagement and learning outcomes. However, there remains a notable gap in the literature regarding the combined effects of AR with structured pedagogical strategies such as guided inquiry and innovative presentation formats like Pecha Kucha. This study seeks to address this gap by examining the synergistic impact of these methodologies on students’ comprehension of complex biological processes, specifically meiosis. By harnessing the interactive capabilities of AR and the concise, engaging nature of Pecha Kucha presentations, our research introduces a novel approach that not only fosters a deeper understanding but also promotes critical thinking, collaboration, and sustained academic interest. This study’s findings can inform future educational practices and contribute to the development of more effective, technology-enhanced learning environments.

2. Materials and Methods

The research used the experimental method with a quasi-experimental design. The quasi-experimental design is applied when using school-defined classes, as determined by the school administration, making random assignment of students to groups unfeasible [47]. Consequently, randomness was only applied in the assignment of the Experimental (EG) and control groups (CGs), involving 3 intact 11th-grade classes from a secondary school in Lisbon [47]. The classes were taught by two teachers, one of whom was the first researcher (class A-CG) and the other two (EG) by a colleague with the same years of teaching practice. The experimental method, with a quasi-experimental design, was used because it is the most appropriate approach when one wants to evaluate the impact of an intervention on students’ academic results or even on other variables [48,49]. The experimental method is the only one that allows establishing a causal relationship between variables, one being the cause (independent variable), in our case, the use of AR associated with a certain teaching strategy, and the other being the effect (dependent variable), which, in our case, was the students’ results in knowledge tests. Of course, this method, like any other, is subject to various sources of error. To ensure the study’s validity, classes/groups were chosen at random, attended the same school, had a similar age and gender distribution, and whose school results were also similar. We can say that the groups are equivalent in these variables. The procedure was the same in the experimental classes/groups (EGs) and control group (CG) except that, in the EG, the AR was used, and, in the control, it was not. Reliability was guaranteed by developing a knowledge assessment test that followed the methodology of classical test construction theory, taking Bloom’s cognitive taxonomy into account, in preparing the items. When evaluating knowledge, it is not advisable to determine Cronbach’s alpha, which is a precise indicator to determine the reliability of results obtained in questionnaires and scales.

2.1. Experiment Plan

The organisation of the experimental group (EG) and control group (CG) in the two 11th-grade classes, corresponding to a total of 65 students with an average age of 16 years, is shown in Table 1.
The three existing 11th-grade classes were included to address ethical equity issues; however, the data from class C were excluded from the analysis due to the small number of participants (only seven). This decision is based on the fact that this number is much lower than the recommended 30 [47] for a sample size that allows for adequate statistical analysis to verify an effect or obtain an analysis of the precision of that effect [50]. Thus, the data from this class were excluded, leaving a total of 58 students. The CG (A) consisted of 30 students, of which 53.3% (n = 16) were male and 46.7% (n = 14) were female. The EG (B) consisted of 28 students, of which 64.3% (n = 18) were male and 35.7% (n = 10) were female. The average age of the control (A) and experimental (B) groups was 16 years.
The work plan for the two classes was organised as illustrated in Table 2.

2.2. AR App División Meiótica 3D

The app was accessed through the official spaces of each operating system and installed by the students with the permission of their parents or legal guardians. The teachers downloaded the manual available on the website (only the Spanish manual includes the plans) to print on cardboard and assemble the dodecahedron that presents the markers to activate the various phases of meiosis in AR. Figure 1 shows the students using the app during the lesson.

2.3. Knowledge Assessment Tests

To control extraneous variables, care was taken to prepare the use of the AR app with the EG teacher, and both teachers followed the same steps of guided inquiry in class. During the lessons, each teacher in their class clarified the students’ doubts, guiding them in finding the correct answer without providing a direct answer. The classes were assessed at two points after the intervention through individual written assessments with items organised according to Bloom’s taxonomy (1956) in an elementary level (E)—appealing to memorisation and reproduction of knowledge—an intermediate level (I)—appealing to understanding, interpretation, and application of knowledge to routine situations, and a complex level (C)—appealing to argumentation, value judgement, application of knowledge to new situations, and problem-solving strategies. In the first instance, a test with eight items was applied: three multiple-choice, two objective responses, one sequencing, one matching, and one production. The second instance, applied fifteen days later, consisted of a group integrated into a global assessment test. This group included 10 items: six multiple-choice, one objective response, one matching, one sequencing, and one production.
Table 3 presents examples of the items used in the knowledge assessment moments, prepared by the teachers.
The Classical Test Theory was used to determine the difficulty of each item, with values ranging from 0 (item not accessible at all) to 1 (item very accessible) and the discrimination parameter, with values ranging from −1 to +1 [51,52]. A discrimination value of −1 indicates that the item is inversely discriminative, meaning that subjects with higher scores on the item find it more difficult to answer compared to those with lower scores. A value of 0 reveals inadequate discrimination of the item among subjects, and a value of +1 indicates that the item is highly discriminative, meaning that subjects with better ability are more likely to answer the item correctly, while those with lower ability are less likely to do so.
The average difficulty value for the items in the post-test was 0.39 and in the follow-up was 0.74, which can be considered within the recommended range. The discrimination values for the items in the post-test were 0.49 and, in the follow-up, were 0.54, values that reflect acceptable discrimination.

2.4. Statistical Analyses

To assess the normality of the distributions we used the Shapiro–Wilk test, rather than the Kolmogorov–Smirnov test, due to our small sample size (less than 50) [53,54]. Additionally, we used the Levene test to evaluate the homogeneity of variances [55]. These tests are crucial because many parametric statistical tests, such as the t-test, assume that the data follow a normal distribution and that variances are equal across groups. By confirming these assumptions, we can confidently apply these statistical methods and ensure that our results are accurate and meaningful. If these assumptions were violated, it could lead to incorrect conclusions, thus compromising the integrity of our findings. Independent samples t-tests and paired samples t-tests were performed to answer our research questions.

3. Results

First, the descriptive statistics are presented, followed by the inferential statistics of the results obtained by the classes in the post-test and follow-up tests. To define the appropriate statistical tests to use, the existence of normality was determined using the Shapiro–Wilk test and homogeneity of variance using the Levene test. Skewness and kurtosis values were also used to confirm the normality of the result distributions.
Once normality and homogeneity of variance were verified, the parametric Student’s t-test was applied. Table 4 presents the descriptive statistics for the post-test and follow-up tests in both classes.
In both tests, a better performance can be observed among the EG students who integrated AR into their learning. This difference is more evident in the assessment closer to the intervention and less pronounced in the follow-up test.
Table 5 presents the Shapiro–Wilk test values with a p value greater than 0.05, as the number of observations is less than 50 [54,56]. The value obtained in the EG for the follow-up test compromises normality (p < 0.05), which led to the confirmation of normality through skewness and kurtosis values, which were confirmed to be between −2 and +2 [57].
The analysis of the homogeneity of variance, whose values [54], obtained using the Levene test, were, for the post-test, F = (1,56) = 0.012, p = 0.913, and, for the follow-up test, F = (1,56) = 0.014, p = 0.900, allow for the acceptance of H0, thus confirming the homogeneity of variance. These results permit the use of parametric statistical tests, specifically, Student’s t-test.

3.1. Students Learning Performance on Post-Test (Q1)

First, the result of the Student’s t-test for independent samples was determined, as presented in Table 6, which sought to determine if there was a significant difference between the academic performance in the post-test of the EG students, who integrated AR into their learning, and the performance of the CG students, who did not use it.
The analysis of the values in Table 6 shows that the EG achieved a better average academic performance equal to 123.39 and a standard deviation of 37.39, compared to the CG’s average value of 102.83, with a standard deviation of 38.07. The t-value of −2.07 indicates better results in the EG compared to the CG, and with a p value less than 0.05, it is accepted as a statistically significant difference between the groups. Thus, it can be concluded that there is an advantage in integrating AR into meiosis learning associated with guided inquiry and the Pecha Kucha technique when students are assessed immediately.

3.2. Students Learning Performance on Follow-Up Test (Q2)

Table 7 presents the results of the application of the Student’s t-test for independent samples, which sought to determine if there was a significant difference between the follow-up test performance of the EG students compared to the CG students.
An analysis of the values in Table 6 shows that the EG achieved a better average academic performance in the follow-up test, with 154.79 and a standard deviation of 40.37, compared to the CG’s average value of 144.30, with a standard deviation of 40.70. The t-value of −0.98 indicates slightly better results in the EG compared to the CG, but with a p value greater than 0.05, H0 must be accepted, meaning that there are no statistically significant differences between the results of the two groups. These results show that, over time, the effect of using AR does not translate into more lasting learning in the EG compared to the CG.
The effect size value in the post-test was determined, obtaining a Cohen’s d of 0.545, which changes to 0.537 with Hedges’ correction. This value can be interpreted as an intermediate effect, indicating that the integration of AR has a moderate impact. However, in the follow-up test, a Cohen’s d of 0.259 was obtained, which changed to 0.255 with Hedges’ correction, interpreted as a small effect. It can be stated that the use of AR in short-term knowledge retention has a slight advantage for the students who used it compared to those who did not; however, this difference diminishes in the long term.

3.3. Students Learning Performance When Using AR with Guided Inquiry and Pecha Kucha (Q3)

Next, the result of the Student’s t-test for paired samples was determined, as presented in Table 8, which sought to determine if there was a significant difference in academic performance between the post-test and the follow-up test of the EG students, who integrated AR into their learning.
An analysis of the values in Table 8 shows that a better average academic performance was obtained by the EG students in the follow-up test, with an average of 154.79 and a standard deviation of 40.37, compared to the post-test value, with an average of 123.39 and a standard deviation of 37.39. The t-value of −3.96 indicates better results in the follow-up test compared to the post-test, and with a p value less than 0.001, which indicates statistical evidence of a difference between the assessments. These values prove that there was an advantage in integrating AR associated with guided inquiry and the Pecha Kucha technique, resulting in better long-term learning outcomes.

3.4. Students Learning Performance When Using Only Guided Inquiry and Pecha Kucha (Q4)

Table 9 presents the results of the application of the Student’s t-test for paired samples, which sought to determine if there were significant differences between the academic performance in the post-test and the follow-up test of the CG students, who did not integrate AR into their learning.
An analysis of the values in Table 9 shows that better average performance was obtained by the CG students in the follow-up test, with a value of 144.30 and a standard deviation of 40.70, compared to the post-test value of 102.83 and a standard deviation of 38.07. The t-value of −5.03 indicates better results in the follow-up test compared to the post-test and has a p value of less than 0.001; therefore, it can be stated that there is a statistically significant difference between the results from the post-test to the follow-up test in students who are part of the CG. These values allow us to consider that there are learning advantages with the use of guided inquiry associated with Pecha Kucha, which resulted in more lasting learning outcomes.
The effect size value was determined in both groups, obtaining a Cohen’s d of 0.748 for the CG, which changed to 0.727 with Hedges’ correction, and a Cohen’s d of 0.919 for the EG, which changed to 0.895 with Hedges’ correction, both values being understood as having a high effect. These values confirm a statistically significant difference between the two assessment moments in both groups, with better results in the follow-up test, leading us to consider more lasting learning.
In summary: It seems that associating guided inquiry with the Pecha Kucha technique produces good results in acquiring and retaining knowledge about meiosis in both groups, and these results were statistically significant. The association of AR improves short-term learning, but the long-term effect is minimal as the EG results proved when compared with the results of the CG.

4. Discussion

This study is innovative due to the integration of AR associated with the guided inquiry teaching strategy, along with the inclusion of the Pecha Kucha method, as no identical studies have been found. The use of AR applications enhances the learning of abstract and non-visible concepts, particularly in Biology education, such as those related to DNA, as it facilitates their conceptual demonstration [44,58,59]. Studies where AR is associated with inquiry are still recommended for further investigations, particularly with larger samples [14]. Conversely, in works where AR was integrated into cell division learning, new investigations are suggested for different school years, including qualitative studies [8]. Regarding guided inquiry, it is important to highlight the significance of providing guidance to students, understood as “activating or constructing appropriate knowledge to be used for making sense of new incoming information” and “integrating new incoming information with an appropriate knowledge base”, as “Pure discovery can be ineffective when it fails to promote the second criterion” [60] (p. 15). The choice to guide students in the learning process is an aspect to consider, given the possibility that students may freely alter the proposed learning sequence, which does not yield good results [61,62]. Another aspect to consider is the use of the Pecha Kucha technique, which supports students in producing a final product that associates the images they selected with oral narration in a sequence that provides an opportunity to showcase what they have learned [18,20,63,64], whether or not AR is used.
At this point, we revisit the research questions to verify if they were fully or partially answered.
Q1, which sought to determine if there were differences in academic performance in the post-test between students who used AR compared to those who did not, was positively answered. The results obtained allowed us to verify the existence of a statistically significant difference between the EG and the CG, with an advantage in the EG’s performance, resulting in a t-value of −2.07, with a p value of less than 0.05. It seems advantageous to integrate AR in this learning context. Our findings are corroborated by other studies, which found that AR, when enhancing the context of inquiry-based learning, translates into cognitive success for students [14].
This analysis was complemented by determining the effect size calculated through Cohen’s d, with a value of 0.545, which changed to 0.537 with Hedges’ correction. These values allow us to state that there was an intermediate effect, meaning that the integration of AR has a moderate impact on short-term learning. This finding is also mentioned in a quasi-experimental study conducted with 103 students, where the authors indicate the effectiveness of AR use “for initial learning rather than reinforcing learning” [44] (p. 180).
The response to Q2, which sought to verify the differences in academic performance in the follow-up test between the EG and the CG, was not positively answered. Despite the better performance of the EG students, with an average of 154.79 and a standard deviation of 40.37, compared to the CG’s average value of 144.30, with a standard deviation of 40.70, the t-value obtained in the test was 0.98, which indicates a slightly better result in the EG compared to the CG, but with a p-value of 0.165, and, therefore, greater than 0.05; thus, it cannot be considered that there is a statistically significant difference between groups. This result is similar to that obtained in another study [65], where the authors, evaluating according to Bloom’s taxonomy, considered the integration of AR advantageous at the analysis level but not at the recall and comprehension levels. However, our findings differ from other studies on the use of AR in studying cell division, which report better outcomes in the EG compared to the CG, and even note an intermediate effect size [8,11].
Q3, which posited that there could be differences in learning between the post-test and the follow-up test in students who integrated AR into their learning, was positively answered. The students’ performance improved from the post-test to the follow-up test, with a t-value of −3.96, with a p value less than 0.001. The negative value indicates a better result in the follow-up test compared to the post-test, and the p value allows us to consider the difference between the two assessments statistically significant. It can be assumed that the integration of AR in this learning context promotes more lasting results [7,66]. In the analysis of the effect size, a value of d of 0.919 was obtained, which changed to 0.895 with Hedges’ correction, indicating a high effect. This value confirms the existence of a statistically significant difference between the two assessment moments, with better results in the follow-up test. This suggests that lasting learning occurred when guided inquiry was combined with AR and Pecha Kucha. This finding contrasts with the aforementioned study in Q1, where the authors only observed immediate reinforced learning [44].
Finally, Q4 was positively answered. This sought to verify the existence of differences between the post-test and the follow-up test in students who did not use AR (the control group) but used the same teaching strategy–guided inquiry, integrating Pecha Kucha, as the EG students. In the follow-up test, the average was 144.30, with a standard deviation of 40.70, and was higher compared to the post-test value of 102.83, with a standard deviation of 38.07. The t-value of −5.03 indicated a better result in the follow-up test compared to the post-test, with a p-value value less than 0.001, meaning that there was a statistically significant difference in results. These values allow us to consider that there is an advantage in the acquisition and retention of knowledge about meiosis when guided inquiry is used, associated with the Pecha Kucha technique. The effect size obtained a Cohen’s d of 0.748, which changed to 0.727 with Hedges’ correction, revealing a high effect. These results are corroborated by previous studies [14,62] on the advantage of using a guided inquiry strategy in student learning if students are guided by the teacher. Identical results are reported in a study on collaborative guided inquiry for learning Biology [28]. It states that this approach helped students articulate hypotheses, make predictions, and record interpretations, thereby enhancing their understanding. It also encourages students to foster deeper discussions, allowing them to compare hypotheses and collectively evaluate evidence. This approach helps students focus on pertinent biological questions and adopt scientific investigation strategies. The main conclusion of this research is that the guided inquiry teaching strategy, combined with the Pecha Kucha presentation method, significantly enhances student learning outcomes in the study of meiosis. Key findings indicate that this combination yields positive short- and long-term learning results, demonstrating its effectiveness in fostering a deeper understanding.
Furthermore, the integration of augmented reality (AR) with this teaching strategy improves short-term performance; however, these benefits diminish over time compared to the students who did not use AR. This suggests that while AR can enhance immediate engagement and comprehension, its long-term impact may not be as robust. The study underscores the necessity for the further exploration of this pedagogical approach across different educational levels and various Biology topics, highlighting the potential of guided inquiry, Pecha Kucha, and AR in enriching science education and promoting sustained learning.

5. Conclusions

This research highlights the effectiveness of guided inquiry, combined with Pecha Kucha and AR, in promoting meaningful learning about meiosis. The results showed that integrating this approach improved students’ long-term knowledge acquisition and retention performance. The comparison between the experimental and control groups revealed statistically significant differences, demonstrating that AR enhances the short-term understanding of complex concepts when used as an educational support tool. This research emphasises the importance of the teacher’s role in promoting active learning [67,68], providing the necessary guidance for students to explore and construct knowledge autonomously and with scientific validity. The combination of active methodologies and emerging technologies, such as AR, proves promising for science teaching, suggesting that future research should be conducted in different educational contexts and on other topics to consolidate and expand the observed benefits.

Author Contributions

Conceptualization, A.F. and G.L.M.; methodology, A.F. and G.L.M.; software, A.F. and G.L.M.; validation, A.F. and G.L.M.; Formal analysis, A.F. and G.L.M.; investigation, A.F. and G.L.M.; resources, A.F. and G.L.M.; data curation, A.F. and G.L.M.; writing–original draft preparation, A.F. and G.L.M.; writing–review and editing, A.F. and G.L.M.; visualization, A.F. and G.L.M.; supervision, G.L.M. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by National Funds through FCT-Portuguese Foundation for Science and Technology, I.P., under the scope of UIDEF-Unidade de Investigação e Desenvolvimento em Educação e Formação, UIDB/04107/2020, https://doi.org/10.54499/UIDB/04107/2020.

Institutional Review Board Statement

The research received a favourable decision from the Ethics Committee of the Instituto de Educação da Universidade de Lisboa.

Informed Consent Statement

The research took place in a school whose principal authorised it and where all the students whose data were collected had the written informed consent of their parents or legal guardians to participate and publish analysed data.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Information 15 00566 g001
Figure 1. Use of AR during the lesson.
Figure 1. Use of AR during the lesson.
Information 15 00566 g001
Table 1. Characterisation of the classes involved in the study.
Table 1. Characterisation of the classes involved in the study.
Class (Group)ARMaleFemaleN TotalAverage Age
A (control group)no16143016
B (experimental group)yes18102816
C (experimental group)yes16716
Total 35306516
Table 2. Organisation of work in classes and assessment moments.
Table 2. Organisation of work in classes and assessment moments.
EGCG
First 90-Min Lesson
Orientation: Inform students that the work will be done in groups of three, with support from the manual, internet research using the Search Coach integrated into Teams, to answer the research problem presented. Explain that they will create a PowerPoint as the final product, according to the Pecha Kucha methodology (exclusively images representing the meiosis process with narration), with a limit of 11 slides and 20 s of narration per slide.
Conceptualisation: The defined research question was “How does cell division by meiosis takes place?”
Investigation: Students used the manual and the internet, exclusively using the Search Coach integrated into Teams, to research and gather information, which they organised and recorded in a Word document submitted on Teams.
Conclusion: Students created the PowerPoint, using the Pecha Kucha methodology to present the cell division process by meiosis, based on the collected information.
Used the División Meiótica 3D app that triggers AR through markers.No use of the AR app.
second 90-min lesson
Discussion: Each group made a 3-min and 40-s presentation (20 s per slide). At the end of each presentation, a feedback session was provided by peers and the teacher.
post-test moment
An assessment composed of eight items.
follow-up moment (fifteen days later)
The global test included a group of ten items on meiosis.
Table 3. Example of items used in the assessments.
Table 3. Example of items used in the assessments.
TypologyItem
E
(multiple choice)		Meiosis has two successive stages, designated as division I and II. The main characteristic of these divisions is that division I
(__) is equational and division II is reductional.
(__) allows DNA replication and division II reduces ploidy.
(__) is reductional and division II is equational.
(__) allows the reduction of ploidy and division II allows DNA replication.
I
(multiple choice)		In the phase where cell 1 is located, the nuclei presents _____ amount of DNA and the set of chromosomes they possess is genetically _____.
(__) the same … identical
(__)the same … different
(__) different … different
(__) different … identical		Information 15 00566 i001
C
(production)		A donkey and a horse are capable of mating and producing offspring, the mule. The mule has 63 chromosomes in its cells, with the donkey father having 62 chromosomes and the horse mother having 64.
Explain why the mule is unable to produce gametes and therefore cannot have offspring.
Table 4. Descriptive statistics for the classes in the post-test and follow-up test.
Table 4. Descriptive statistics for the classes in the post-test and follow-up test.
Class (Group)ARPost TestFollow-Up
MDPMinMaxMax
Possible		MDPMinMaxMax
Possible
A (CG)no102.8338.0740185200144.3040.7061200200
B (EG)yes123.3937.3965190200154.7940.3761200200
Table 5. Shapiro–Wilk test of normality, skewness, and kurtosis.
Table 5. Shapiro–Wilk test of normality, skewness, and kurtosis.
Class (Group)-TestStatisticdfpSkewnesspKurtosisp
A (CG)–post-test0.955300.2310.3580.427−0.6190.833
B (EG)–post-test0.951280.2090.1520.441−1.1650.858
A (CG)–follow-up0.942300.101−0.1090.427−0.8840.833
B (EG)–follow-up0.915280.027−0.6400.441−0.4950.858
Table 6. Independent samples: t-test analysis of post-test scores.
Table 6. Independent samples: t-test analysis of post-test scores.
Class (Group)-TestNAverageSDtp
A (CG)–post-test30102.8338.07−2.070.021
B (EG)–post-test28123.3937.39
Table 7. Independent samples: t-test analysis of follow-up test scores.
Table 7. Independent samples: t-test analysis of follow-up test scores.
Class (Group) TestNAverageSDtp
A (CG)–follow-up30144.3040.70−0.980.165
B (EG)–follow-up28154.7940.37
Table 8. Paired samples: t-test analysis of post-test and follow-up test scores for EG.
Table 8. Paired samples: t-test analysis of post-test and follow-up test scores for EG.
TestNAverageSDtp
Post-test28123.3937.39−3.96<0.001
Follow-up28154.7940.37
Table 9. Paired samples: t-test analysis of post-test and follow-up test scores for CG.
Table 9. Paired samples: t-test analysis of post-test and follow-up test scores for CG.
TestNAverageSDtp
Post-test30102.8338.07−5.03<0.001
Follow-up30144.3040.70
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Faria, A.; Lobato Miranda, G. The Effect of Augmented Reality on Learning Meiosis via Guided Inquiry and Pecha Kucha: A Quasi-Experimental Design. Information 2024, 15, 566. https://doi.org/10.3390/info15090566

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Faria A, Lobato Miranda G. The Effect of Augmented Reality on Learning Meiosis via Guided Inquiry and Pecha Kucha: A Quasi-Experimental Design. Information. 2024; 15(9):566. https://doi.org/10.3390/info15090566

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Faria, António, and Guilhermina Lobato Miranda. 2024. "The Effect of Augmented Reality on Learning Meiosis via Guided Inquiry and Pecha Kucha: A Quasi-Experimental Design" Information 15, no. 9: 566. https://doi.org/10.3390/info15090566

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