INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XII December 2025  
Real Data, Real Learning: Experiential Learning Strategies in  
Corporate Finance Education  
*Nur Syuhada Jasni  
Faculty of Accountancy, Universiti Teknologi MARA, Cawangan Selangor, Kampus Puncak Alam,  
Selangor, Malaysia  
*Corresponding Author  
DOI: https://dx.doi.org/10.47772/IJRISS.2025.91200038  
Received: 11 December 2025; Accepted: 18 December 2025; Published: 31 December 2025  
ABSTRACT  
Theory and practice in corporate finance education are often disconnected. Prior research on Problem-Based  
Learning (PBL) in finance holds some potential, but the evidence for the influence of experiential, data-driven  
tasks on students’ conceptual understanding and data literacy remains under investigated. The study adopted  
Kolb’s Experiential Learning Theory and analyzed a PBL project using 59 accounting students representing  
equity analysts at a Malaysian public university to implement the Efficient Market Hypothesis (EMH) on  
actual Bursa Malaysia event data. The study is qualitative in design. Descriptive statistics were used to  
summarise student endorsement of the project, and written reflections collected over five months in 2024 were  
analysed thematically. Two research questions guided the analysis: (1) how the project shapes students’  
understanding of EMH and related corporate finance concepts; and (2) how it influences students’ data  
literacy, including their use of spreadsheets to analyse and interpret investment outcomes. Results demonstrate  
strong support for the intervention, with 91.5% of students recommending the project for future cohorts. Six  
themes were identified: authentic relevance, improved analytical skills and data-handling, theory-to-practice  
transfer, increased self-confidence and decision-making, stronger communication and collaboration, and  
perceived deficits in instructional scaffolding. Results show that a systematic interaction with real market data  
deepens conceptual understanding and enhances the competence of the quantitative evidence used, making  
visible the design features that can be improved. The study introduces an EMH-based PBL model for corporate  
finance modules and proposes design protocols for finance educators desiring to cultivate both technical  
proficiency and workplace skills through experiential techniques.  
Keywords: Corporate finance education, Experiential learning, Data literacy, Higher Education  
INTRODUCTION  
The gap between theory and practice in corporate finance programs has long been a concern for educators and  
employers. Although lectures teach students basic concepts, classroom instruction often stops at procedural  
thinking, decision-making, or teamwork, which are increasingly important in finance. Hence, graduates leave  
university with solid theoretical knowledge but limited experience in synthesizing data, comparing investment  
alternatives, and making rational decisions under uncertainty. Studies in finance and accounting education  
report weak development of higher-order thinking, communication, and teamwork skills, despite their  
importance in contemporary finance work (Hmelosilver, 2004; Sousa & Costa, 2022). These concerns  
highlight the need for curricula centred on authentic tasks, real-world datasets, and structured opportunities for  
sustained learning.  
Theory and practice education gaps have recognized frameworks of experiential learning theory and authentic  
learning models. Within, these PBL, or problem- based learning, entered the educational discourse as an  
educational model that centres on and promotes active and self-regulated learning, learning supervised in  
collaboration with others to solve and learn from problems, and inquiry learning (Stanley & Marsden, 2012;  
Silva, Bano, & Daugherty, 2018). PBL has exposed students to authentic problems from their real lives that  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XII December 2025  
correspond to the multidimensional and complex problems they will encounter in their future careers. Learners  
connect disciplinary knowledge, dispute their assumptions, reach consensus, and justify their position. Positive  
relationships have been reported between skills development through PBL and outcomes such as critical  
thinking, analytical reasoning, self-directed learning, motivation, and relevance (Sugeng & Suryani, 2020;  
Hmelo-Silver, 2004), as noted in previous work in finance and related disciplines. All together, they are  
closely aligned with advanced corporate finance curricula, especially in capital-budgeting analysis, market  
inefficiency and market anomaly assessments, and optimisation of discretionary resource allocation, which all  
feature analytical and normative ambiguities. Such structures are critical for Problem-Based Learning (PBL). It  
is essential to note that, although PBL is being introduced into corporate finance education, it also presents a  
range of problems to be solved.  
In addition, students, including those with less quantitative skills, face difficulties when learning basic  
concepts that cannot be solved independently (Sugeng & Suryani, 2020; Silva et al., 2018). This highlights the  
necessity of building finance classes with a high level of self-determination as well as guidance. In addition,  
poorly designed tasks and the unbalanced composition of the groups result in high activity and low reasoning  
power, as well as low motivation and unequal participation (Borah et al., 2023). PBL, combined with  
traditional teaching methods and curricular design, illustrates that a holistic and integrated approach to  
teaching is needed. The intentional structuring of courses like this aims to facilitate the understanding of  
cognitive concepts embedded in finance courses and reduce performance gaps. Despite widespread discussion  
of enhancing accounting and finance courses, their curricula remain firmly rooted in lectures and textbook  
problems. Graduates also say they struggle to understand actual financial information, use principles like EMH  
and market behaviour to make decisions in uncertainty.  
Most existing works on finance pedagogy discuss definitions of active learning methodologies, whereas very  
little design-informed research demonstrates the impact of structured PBL, using real market data, on the  
development of data literacy and higher-order capabilities. This gap is the current motivation of the thesis,  
which considers how a data-driven PBL project in a corporate finance module addresses the gap between  
theory-based content and the relevance of professional skills. The aim is to explore how PBL, interacting with  
actual capital-market data, contributes to the acquisition of real data literacy, analytical reasoning, and  
conceptual understanding of economic fundamentals, with a focus on the Efficient Market Hypothesis (EMH).  
The second goal is to investigate how students perform with PBL blended with targeted instruction and  
conventional teaching techniques, including perceived relevance, working collaboratively within the team, and  
confidence in working with market information.  
Following Kolb’s Experiential Learning Theory (ELT), the study addresses two questions; (RQ1) How do  
students describe the impact of a PBL project using authentic Bursa Malaysia data on their understanding of  
key corporate finance concepts such as EMH and market anomalies and (RQ2) How does participation in the  
project impact the students’ data literacy, including data interpretation, use of spreadsheet-based analysis, and  
evaluation of investment outcomes. The study is structured as follows: the next section presents a literature  
review, the subsequent section outlines the research methodology used, and the findings are then discussed.  
The last section of the study presents the conclusion.  
LITERATURE REVIEW  
Kolb’s Experiential Learning Theory as a Framework for Learning  
Kolb’s Experiential Learning Theory fits well within the framework of embedding pedagogy within a course,  
given its influence within the field. The learning process has four stages and begins with the Concrete  
Experience, where the learner engages with the material. Then, the student reflects on the experience through  
Reflective Observation. The next two stages are where the learner synthesizes and plans through the Abstract  
Conceptualization stage and then tests their work through Active Experimentation - where they engage with  
the real world. This process forms a cycle of learning and understanding, facilitating knowledge transfer (Kolb,  
1984).  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XII December 2025  
Due to the hands-on learning styles of accounting and finance, experiential learning has been adopted by other  
disciplines to meet industry needs that require graduates with versatile and hands-on skills (Gittings et al.,  
2020; Rajeevan, 2020). Rather than traditional lectures, teachers use case studies, live projects, or simulations,  
which place students in the role of using real decisions. This enhances the cognitive domain, as well as  
teamwork and communication, which are in-demand soft skills in the industry.  
Involving finance students in the analysis of historical trading data using statistics is an example of assignment  
integration outlined by Pan et al. (2016). The process is a perfect example of Kolb’s cycles. The students  
started by working with the data (Concrete Experience). Afterwards, they iterated through multiple stages of  
the cycle by reflecting on the results, theory, and application of the results through decisions. Van Akkeren and  
Tarr (2021) also demonstrated to students how regulatory frameworks can be combined with ethical judgment  
through reflective and real-world experiential projects.  
There were improvements in academic attainment and understanding of the concepts by Leal-Rodríguez and  
Albort-Morant (2019). Flynn and McCarthy (2016) reported that the integration of theory and practice in a real  
corporate finance project spurred students to engage. Data literacy and skills in interpretation were also  
addressed using Kolb’s model, as explained by Olsen (2024), with a focus on IPOs and similar tasks. The  
resultant data is representative of how experiential learning increased the ability to bridge theory and practice  
in developing reflective thinking. Research suggests that experiential learning enhances students' analytical  
reasoning, reflective practices, and collaboration skills (Ahmed, 2019; Tran & Herzig, 2024). In simulated and  
real-world finance problems, Sousa and Costa (2022) and Bakoush (2022) observed that students display more  
motivation and a higher level of engagement.  
Etling et al. (2023) demonstrated that group work facilitated the development of soft skills among finance  
professionals. They are technology-driven and have an equal potential to open up new opportunities for  
students. Kottara et al. (2025) discuss the importance of blended learning environments that combine digital  
simulations with collaboration to utilise complex data sets and to prepare students with analytical skills and  
technology in a professional environment. Still, challenges remain. Underdeveloped cooperative activities may  
lead to differential efforts, confusion, and time burden (Butler et al., 2019; Tran & Herzig, 2024). Lacking  
proper support, students with lower quantitative competencies are at risk of failing to comprehend fundamental  
concepts (Sugeng & Suryani, 2020; Silva et al., 2018). With these gaps in mind, Borah et al. (2023) support a  
hybrid approach that combines experiential learning with a more traditional learning model. This way, students  
acquire both practical skills and relevant theoretical knowledge.  
Application of ELT in The Current Study  
This study applies Kolb’s ELT as the framework. Following the completion of a PBL project wherein  
participants analyzed four years (2019–2022) of stock prices, students then carried out event studies, and  
finally, they interpreted the findings in the context of the EMH. All four of Kolb's learning cycles were  
incorporated into the project. These cycles include Concrete Experience (real market data), Reflective  
Observation (the results and EMH), Abstract Conceptualization (the theory), and Active Experimentation (the  
practical investment advice). To solve numerous problems, a model was created that included scaffolding  
templates, instructions, and collaborative learning, allowing students to work on a more advanced, levelled  
task while still utilising their basic skills. This research, in the context of Malaysian higher education, aims to  
investigate the role of ELT in integrating real-world data into finance teaching, a relatively underexplored area  
in South East Asia.  
RESEARCH METHODOLOGY  
The sample from our investigation consisted of 59 accounting students enrolled in a corporate finance course  
at a university campus in Malaysia. In groups, during the time period March to July 2024, the students selected  
a publicly listed Malaysian company, acquired the stock price information on the Malaysian company from  
2019 to 2022, and conducted an event study to analyze the effect on the stock market of the company’s  
announcements. Each team had to justify its results using the Efficient Market Hypothesis (EMH)  
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
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The students were given an extensive description of all their tasks, datasets, and templates, but were also  
allowed the discretion to explore how they would like to analyse the data. It allowed students to practice  
making autonomous decisions, a critical skill for a finance career. These two elements helped students sharpen  
their analytical abilities alongside their professional judgement! It enabled students to select the depth to which  
the investigation could proceed and personalizability of engagement and skill development based on their  
learning preferences (Mavruk, 2025; Pereira et al., 2020). Students also acquire professional communication,  
negotiation and teamwork skills, which are necessary in finance, when they work as a group.  
The skills development was measured using surveys composed of both closed-ended and open-ended questions  
(Syahril et al., 2021; Uotila et al., 2023). Closed responses were reported with descriptive statistics. Open-  
ended responses were imported into ATLAS.ti and analysed thematically as used in current experiential  
learning research work. The stages of the methodological framework for developing data literacy skills are  
outlined in Figure 1. The objective of this initiative is to utilise real financial records from Bursa Malaysia,  
gradually exposing students to real-world data experiences.  
1. Exposure (Concrete Experience) - Students should gain an understanding of data structures and be able  
to apply this knowledge to new data or real-world scenarios.  
2. Exploration (Reflective Observation) - The data will be analysed and visualised using statistical and  
spreadsheet tools. The students would use statistical or spreadsheet tools to notice patterns, outliers,  
and associations. They will observe and analyse the data as it is processed. Students are to reflect with  
some guidance and develop preliminary interpretations and awareness of the data behavior.  
3. Conceptualization (Abstract Conceptualization) - Students relate the patterns with the financial theories  
and the Efficient Market Hypothesis. EMH will be the touchstone to this phase where the students  
interpret the theoretical assumptions and articulate how the empirical evidence supports or challenges  
the theory.  
4. Application (Active Experimentation) - Theoretical knowledge helps students complete advanced  
tasks. Hypothesis testing, portfolio simulations, and market studies strengthen data literacy through  
practical problem-solving.  
5. Reflection and Evaluation (Meta-Cognitive Integration) - Students analyze their work and determine  
the strengths and challenges. They will assess themselves with the goal of growing data reasoning and  
confidence, while the feedback will help them reflect. The focus will be analytical processes.  
Figure 1. Methodological Process for Developing Data Literacy  
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RESULTS AND DISCUSSION  
Overall student feedback for the project was positive, with 91.5% of the students supporting, 5.1% somewhat  
supportive and 3.4% opposed; unlike the first group, the last two groups were in the minority. Word frequency  
revealed that the project focused on ‘real world’ “financial” (18) and “efficiency” (16), as well as “financial”  
(11) “decision” making, at which the students put in major effort since this project was centered on finance.  
These studies confirm previous research that demonstrates the need to integrate real-world challenges into  
finance education to maintain students' interest. (Flynn & McCarthy, 2016; Leal-Rodríguez & Albort-Morant,  
2019).  
Thematic Insights  
Thematic analysis yielded six themes that corresponded to the two research questions and Kolb’s Experiential  
Learning Theory. Themes 1 and 2 address RQ1, specifically the conceptual understanding of EMH and related  
concepts in corporate finance. Themes 3 and 4 concern RQ2 on data literacy. Themes 5 and 6 overlap as they  
demonstrate how confidence and cooperation influence the interpretation of concepts and data. Responses to  
RQ1: conceptual understanding of EMH and market behaviours  
Themes addressing RQ1: Conceptual understanding of EMH and market behaviour  
Theme 1 (RQ1): Authentic market context and conceptual relevance (Kolb: Concrete Experience)  
Students learnt the crux of the knowledge in the context of actual Bursa Malaysia data, which made sense to  
them and put it in an environment they live in, in the real market. One participant stated that the activity "felt  
like real analyst work, not just theory." (P12) and another stated that "market trends made the EMH more real."  
(P18). These comments make it clear that students connected ideas such as EMH and volatility to tangible  
patterns in world prices, rather than just a theory in their textbooks. Similarly, they reported greater motivation  
and also a clearer understanding of the relevance of their work. This trend aligns with other research that  
demonstrates authentic tasks and real-life contexts enhance the perceived relevance and ownership of learning  
in finance courses (Flynn & McCarthy, 2016; Gittings et al., 2020). In the context of RQ1, Theme 1 displays  
that exposure to market data was linked to a greater understanding of corporate finance concepts.  
Theme 2 (RQ1): Theory–practice integration for EMH and anomalies (Kolb: Reflective Observation)  
Students reported that the research helped them to connect formal theory with real market behaviour,  
especially EMH. “EMH felt abstract before; now I try it myself,” one student wrote in a reflection (P04). As  
another person observed, “the results showed that markets are not always efficient.” These reflections  
demonstrate that students made a comparison between theoretical expectations and the outcomes of the event  
study, shifting their learning to meet the expectations. Instead of reiterating the definitions they got of EMH,  
they reflected on the extent to which price responses would match with efficient pricing, but where anomalies  
occurred. This finding is consistent with a study by Van Akkeren and Tarr (2021) and Leal-Rodríguez and  
Albort-Morant (2019), which also found that a more structured engagement with empirical evidence makes  
students more critical when examining dominant finance theories. For RQ1: Theme 2 describes how students’  
reflective work with real data facilitated theory–practice integration.  
The following themes relate to RQ2: Data literacy and spreadsheet-based analysis  
Theme 3 (RQ2): Analytical and spreadsheet-based data literacy (Kolb: Abstract Conceptualisation)  
The project-built skills for working with financial data at a higher level of abstraction. Another participant  
said, “Correlations between stocks make sense to me now” (P14), whereas another reported, “I interpret  
abnormal returns from events” (P08). These statements demonstrate the transition to Abstract  
Conceptualisation, in which ‘raw’ prices are transformed into indicators and patterns. They learned how to  
convert returns, risk metrics, correlation, and output of event studies in Excel into numbers, and what those  
numbers would mean in investment decisions. This finding is consistent with earlier research, which has  
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shown that coursework focused on analytics enhances statistical reasoning when it links learning to real-world  
applications (Pan et al., 2016; Olsen, 2024). In relation to RQ2, Theme 3 demonstrates the importance of data  
literacy in terms of data interpretation and the ability to analyse data in a spreadsheet format as part of the  
development of data literacy.  
Theme 4 (RQ2): Scaffolding needs for data-intensive tasks (Kolb: Supported movement through the  
cycle)  
Although students had similar overall positive experiences, they also reported struggles with tools and pacing  
for experiential activities. While statements like “Excel functions were confusing at first” (P25) and “some  
step-by-step guides would have helped” (P04) suggest that some guidance was absent. These concerns are also  
consistent with research suggesting that students may overwhelm themselves and become disaffected from  
experiential activities when no support is provided for the interaction (Butler et al., 2019; Etling et al., 2023),  
especially if such students lack adequate technical readiness. Some of these issues might have been solved by  
using templates and clearer guidelines, but students still asked for clarification on the scaffolding and some of  
those problems. In response to RQ2, Theme 4 points out that data literacy is more developed when an  
analytical task is constructed, including graduated tasks for functions as well as interpretation.  
Linking understanding and data literacy (RQ1 and RQ2)  
Theme 5 (RQ1 & RQ2): Bringing Confidence and evidence-based decision-making (Kolb: Active  
Experimentation)  
The project instilled great professional confidence and empowered me to make rational, evidence-based  
choices. One student even stated, “I back up my recommendations with empirical data.” (P20). Another  
responded, “My confidence builds when my insights are supported by rigorous analysis” (P2). These  
comments reflect the Active Experimentation phase, where students develop their ideas and analyse them to  
justify their investment decisions. These mastery experiences, grounded in Bandura’s self-efficacy theory,  
explain why students report feeling better prepared to tackle complex financial decisions (Bakoush, 2022).  
Theme 5 presents an articulation of EMH and its associated concepts in a more confident and concept-based  
perspective, providing recommendations for RQ1. For RQ2, the evidence suggests that improved data skills  
led to practical, evidence-informed decision-making, rather than intellectual abstraction.  
Theme 6 (RQ1 & RQ2): Collaborative explanation and communication with others (Kolb: Experience +  
Reflection with peers)  
In terms of conceptual and analytical process, group work (or discussion) was very important for the ways  
students engaged in the development and expression of conceptual and analytic understanding. As one  
participant stated, “We argued on assumptions until arriving at the model agreement” (P09). One said,  
“Explaining my analysis gave me confidence" (P14). These descriptions demonstrate how students employed  
collaboration to cross-examine interpretations with one another and negotiate models, as well as to transform  
numerical results into shared narratives. This finding is consistent with past research, which has shown that  
structured collaborative inquiry promotes more effective learning of soft skills and deeper conceptual  
understanding in education, particularly in accounting and finance (Tran & Herzig, 2024). More specifically,  
regarding RQ1, Theme 6 demonstrates that students were able to refine their conceptual knowledge when they  
explained their interpretation of EMH and anomalies to their peers and gained clarification. With respect to  
RQ2, communication skills become a bridge between spreadsheet outputs and explainable narratives of  
investment decision-making.  
Table 1. Themes, Representative Student Quotes, and Mapping to Kolb’s Experiential Learning Cycle  
Theme  
Representative quotes (anonymised)  
ELT and RQ link  
Theme 1 (RQ1): 1. “Using actual Bursa Malaysia data Concrete Experience.  
Students are  
Authentic  
helped me see how market news affects immersed in real market data and  
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relevance  
market context)  
(real  
share prices.” (P05)  
analyst-type tasks, and thus their  
learning is grounded in real-life  
examples of the professional context.  
This theme informs RQ1 on the way  
students grasp EMH and EMH-related  
concepts in the real world.  
2. “Felt like real analyst work, not just  
theory.” (P12)  
3. “Market  
trends  
made  
EMH  
more  
realistic.” (P18)  
4. “I finally understood volatility from real  
examples.” (P07)  
5. “Authentic data made finance more  
interesting to me.” (P15)  
Theme 2 (RQ1):  
Theory–practice  
connection (EMH  
and concepts)  
1. “Applying  
EMH  
to  
our  
chosen Reflective Observation. Students revisit  
finance theory and contrast predictions  
made by the EMH with what is  
companies was eye-opening.” (P11)  
2. “EMH felt abstract before; now I can test  
observed in actual price movements.  
This theme is directly related to RQ1,  
which demonstrates how students are  
able to reconstruct their understanding  
of EMH alongside market anomalies  
after completing the experiential tasks.  
it myself.” (P04)  
3. “The results showed markets are not  
always efficient.” (P09)  
4. “Linking  
formulas  
to  
actual  
data  
improved my understanding.” (P17)  
1. “This project made EMH feel more real  
and testable.” (P13)  
Theme 3 (RQ2):  
2. “I learned how to calculate returns and Abstract Conceptualisation. Students  
Analytical  
data skills  
and  
risks in Excel.” (P03)  
refine their conceptual knowledge of  
finance and select appropriate methods  
3. “Correlations between stocks now make  
through  
quantitative  
analysis  
and  
sense to me.” (P14)  
statistical interpretation. This theme  
primarily informs RQ2 on data literacy  
and spreadsheet-based analysis.  
4. “I can interpret abnormal returns from  
events.” (P08)  
5. “Data analysis felt challenging but  
rewarding.” (P10)  
6. “I improved in using descriptive statistics  
for finance.” (P21)  
Theme 4 (RQ2,  
with implications  
1. “Excel functions were confusing at first.” Supported movement through the ELT  
(P25)  
cycle. Kolb’s model assumes a balance  
between guidance and autonomy to  
manage cognitive load. This theme  
primarily informs RQ2 by highlighting  
for  
Challenges  
RQ1):  
and  
2. “More training would make this project  
easier.” (P08)  
scaffolding needs  
where  
data  
work  
needs  
clearer  
3. “Time pressure made analysis stressful.”  
scaffolding, and it has implications for  
RQ1 because weak support can limit the  
extent to which students apply EMH  
and related concepts in practice.  
(P12)  
4. “Some results were hard to interpret  
without guidance.” (P17)  
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5. “Step-by-step  
examples would  
have  
helped.” (P04)  
Theme 5 (RQ1 &  
RQ2):  
1. “I feel more confident making investment Active Experimentation. Students apply  
decisions.” (P06)  
conceptual and analytical knowledge to  
construct and defend investment choices  
in realistic scenarios. This theme links  
RQ1 and RQ2 because conceptual  
understanding and data literacy are both  
expressed through more confident,  
evidence-based decisions.  
Confidence  
and  
2. “Now I can justify my recommendations  
evidence-based  
decision-making  
with data.” (P20)  
3. “I am less afraid to analyse financial  
statements.” (P19)  
4. “Decision-making became easier with  
evidence.” (P16)  
5. “I trust my judgment more when backed  
by analysis.” (P02)  
Theme 6 (RQ1 &  
RQ2):  
1. “Teamwork  
helped  
me  
understand Concrete Experience plus Reflective  
others’ approaches.” (P22)  
Observation. Students learn from peers  
Collaboration and  
communication  
through  
discussion,  
feedback,  
and  
2. “Explaining my analysis improved my  
shared meaning-making. Discussing,  
giving, and receiving feedback, as well  
as engaging in meaning-making with  
others, enables students to learn from  
their peers. This thematic support  
informs both RQ1 and RQ2 through  
evidence showing how communication  
enables students to understand financial  
confidence.” (P14)  
3. “We debated assumptions until we  
agreed on the model.” (P09)  
4. “Group  
discussions  
taught  
me  
presentation skills.” (P06)  
concepts  
outcomes  
investment narrative.  
and  
into  
convert  
numerical  
5. “Working in a team made me more  
a
comprehensible  
organised.” (P18)  
CONCLUSION  
Two research questions guided the investigation into the use of authentic Bursa Malaysia data in a PBL project  
and its effect on learning in corporate finance. The first research question (RQ1) inquired about how students  
articulated the effect of the project on their understanding of certain concepts, such as the EMH, capital  
budgeting, and market anomalies. The second research question (RQ2) examined how the students’ data  
literacy (data interpretation, analytical skills using a spreadsheet, and evaluation of investment results) was  
impacted by their participation in the project.  
With respect to RQ1, the results indicate that the students moved from merely rote learning the jargon to  
genuinely understanding the concepts and the context surrounding the learning. Students perceived market  
efficiency, volatility, and patterns of anomalies as empirical problems to be solved rather than merely  
theoretical problems in a textbook. They expressed that the EMH became more tangible and was easier to test,  
and they were able to make better connections between formulas and the observable price behaviour of the  
assets. The project prompted them to question the idealised models often taught when the data encountered is  
noisy and imperfect. This shift is indicative of a movement from mere theory to the application of theory in a  
real market, aligning with the principles of experiential and authentic learning.  
Another learning outcome focus for RQ2 is the enhancement of data literacy skills for students, with a clear  
recognition of learning gains in using Excel for calculations related to returns and risk measures, interpreting  
abnormal returns, and understanding the interrelatedness of numerical results and investment decisions. The  
students expressed improvements in chart reading, interpreting financial news, and advocating for their  
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positions, as well as solving analytical problems. Along with their improvements in data literacy, the students  
noted an increasing absence of structured scaffolding, particularly for those who struggle with quantitative  
concepts. The data-rich tasks were suggested to be time-consuming and appeared to cause an interpretation  
burden, indicating that tasks involving data must be built with several support levels to be usable for all  
students, with minimal to no support at this level.  
The results indicate that with the Kolb-aligned, data-driven PBL design, conceptual understanding and data  
literacy in corporate finance are better supported. The use of genuine financial problems allowed the students  
to be situated in realistic market situations. The analysis of tasks to be guided allowed for the conceptual  
generalisation to be supported and the reflection of the higher-order type to be critically evaluated. Self-  
efficacy was built through the clear and defensible recommendations being obtained and the analysis being  
complemented by the presentation and collaborative group work. The students, who provided constructive  
feedback on the design, especially those with more experience in data tasks and whose scaffolding was limited,  
were the ones who emphasised the value of the tasks most.  
The answer provided by this research is twofold. The results of the study show that the respondents, through  
structured PBL with real market data, developed a more immersive understanding of the core concepts of  
corporate finance and the ability to conduct, analyse, and interpret financial data, and thus responded to the  
two research questions. For curriculum designers, the evidence points to several design priorities: embed live  
or realistic datasets, make explicit links to key theoretical constructs such as EMH, and provide progressive  
scaffolding for analytical tools. Future research on employability outcomes, long-term retention of data  
literacy, and the integration of coding tools such as Python and SQL would help test and extend these findings  
across modules and institutional contexts.  
ACKNOWLEDGEMENT  
The author would like to thank the Faculty of Accountancy at Universiti Teknologi MARA (UiTM) Puncak  
Alam for their invaluable support in facilitating this study.  
Conflict Of Interest Statement  
There is no conflict of interest regarding the publication of this research  
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