Bioinformatics demands professionals skilled in both computing and the biological sciences, yet introducing these interdisciplinary concepts at earlier educational stages remains challenging. Here, we report the insights and perspectives gained from implementing a bioinformatics-focused pilot project programming course for high school students in Belo Horizonte, Brazil. Coordinated by a science teacher with support from university researchers, the course adopted Inquiry-Based Learning (IBL) and gamification methodologies to enhance student engagement. Structured in three phases over 9 months, the curriculum began with Scratch, through which students developed Molecular Biology projects such as DNA transcription simulations and question–answer games. Python was subsequently introduced via conceptual lessons and practical activities. The experience demonstrates that similar initiatives can be replicated in schools with basic technological resources and trained educators, although partnerships with universities or external experts may be required in less resourced contexts. The strategies presented offer guidance for educators and may inspire comparable programs, contributing to the training of future bioinformatics professionals.
bioinformaticsgamificationhigh schoolinquiry-based learningScratchPythonThe author(s) declared that financial support was received for this work and/or its publication. This work was supported by grants from the Fundação de Amparo á Pesquisa do Estado de Minas Gerais (FAPEMIG, projecst APQ-02690-22 and APQ-01838-24) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, project 440307/2022-8).section-at-acceptanceSTEM EducationIntroduction
Recent technological advances have driven sociocultural changes that strongly impact education, particularly through increased connectivity and access to digital devices, reshaping teaching and learning processes (Coll, 2013; Nicolete et al., 2021). Globally, there is a growing movement to integrate computing education into basic education curricula; however, access remains uneven and closely linked to national income, with over 40% of students in high- and upper-middle-income countries having Computer Science as a compulsory subject (Vegas et al., 2021).
One promising approach to developing computational skills is integrating bioinformatics into high school curricula. Bioinformatics combines computer science and life sciences to analyze biological data and is an expanding field facing a shortage of professionals with interdisciplinary training (dos Santos et al., 2023). While initiatives have traditionally focused on higher education (Mariano et al., 2019; de Melo-Minardi et al., 2022), recent studies emphasize the importance of introducing bioinformatics concepts earlier to build foundational skills and stimulate long-term interest (Mariano et al., 2022). In addition, bioinformatics supports the understanding of abstract topics such as genetics and promotes interdisciplinary learning involving Biology, Mathematics, and Computer Science (Marques et al., 2014; Vasconcelos et al., 2022; Castro et al., 2020; Martins et al., 2018), while also connecting education to labor market demands (Lewitter and Bourne, 2011; Marques et al., 2014).
Evidence indicates that integrating bioinformatics into school curricula strengthens the teaching of Natural Sciences (Ou et al., 2023). A notable example is the study by Martins et al. (2020), which proposes activities that enable students to consolidate Molecular Biology concepts while simultaneously engaging with bioinformatics tools. Importantly, the effective inclusion of this field in school programs depends not only on curricular integration but also on systematic teacher training, ensuring that educators are equipped to deliver high-quality instruction in this emerging interdisciplinary area (Marques et al., 2014).
Despite its recognized potential, integrating programming and computational thinking into primary and secondary education remains a considerable challenge. This is not solely due to the need for adequate infrastructure and access to technology but also because it requires educators who are thoroughly trained to effectively deliver interdisciplinary content. Furthermore, teaching programming in isolation may not be sufficient to fully capture students' attention or foster deep understanding. In this regard, the implementation of active learning methodologies, such as Inquiry-Based Learning (IBL) and gamification, emerges as a promising solution. Gamification, defined as the utilization of game elements in non-game environments, has been frequently employed in education in recent years (Zeybek and Saygi, 2024). IBL encourages students to take an active role in the learning process by posing questions, investigating real-world problems, and constructing knowledge through exploration and collaboration (Martins et al., 2017).
Although few studies address the integration of computing into high school, existing research highlights its role in fostering autonomy, creativity, logical reasoning, and interdisciplinary skills (Nascimento, 2009; Nicolete et al., 2021; Silva, 2017). In addition to appropriate methodologies, selecting an educational programming language requires attention to ease of use, intuitive syntax, immediate feedback, and free access (Grandell et al., 2006; Bodin, 2020). This paper reports the design and implementation of a pilot bioinformatics programming course for private high school students in Belo Horizonte, Brazil, integrating core programming skills with molecular biology concepts through IBL and gamification. Organized into modular phases, the curriculum included hands-on activities such as DNA transcription simulations, aiming to develop computational thinking, stimulate interest in bioinformatics careers, and promote an engaging, interdisciplinary science education experience.
Development of the elective course
The course began with a diagnostic questionnaire to assess students' prior programming knowledge. Based on the results, introductory lessons were offered to present fundamental computing concepts, including hardware, software, operating systems, algorithms, binary language, and how computers interpret commands. The curriculum followed a structured progression, starting with the programming environment and good coding practices, and advancing to operators, variables, control structures, functions, methods, and list manipulation (de Melo-Minardi et al., 2022).
After this initial stage, students were introduced to the Scratch programming language through guided activities that familiarized them with the platform and its basic features. They then solved small challenges in molecular biology using code blocks, effectively linking programming logic to biological concepts. To reinforce learning and engagement, competitive activities such as Kahoot (https://kahoot.com) games and embedded multiple-choice questions were used to review both programming and biology content.
As students became more confident with Scratch, they developed interactive projects, culminating in the creation of two games. The first was a collaborative maze game, Cheese Chase (Woodcock, 2019), and the second involved designing an original Scratch program integrating Molecular Biology concepts. Before these final projects, a review lesson on Molecular Biology was conducted, and students selected topics to guide their creations. These projects required the integration of multiple programming blocks, promoting broader computational thinking, creativity, and interdisciplinary learning, while increasing student motivation and autonomy.
Assessment emphasized project completion and increasing complexity rather than solely numerical grades, as this approach proved more appropriate for an elective course and less discouraging for students. At the end of the school year, students were introduced to Python, focusing on fundamental commands and structures such as variables, conditionals, loops, functions, and logical operators. These concepts were applied in Molecular Biology–related challenges, with explicit comparisons to Scratch to support understanding. All projects were evaluated according to the school's guidelines, and the overall development is summarized in Supplementary Figure S1.
The Inquiry-Based Learning (IBL) methodology was applied in both Scratch and Python activities, emphasizing its investigative nature. Each content block began with a brief theoretical explanation, during which the instructor introduced fundamental concepts and presented a corresponding challenge within the first 20 min of class. Over the next 30 min, students engaged with the challenge, actively exploring the topic while the teacher served as a facilitator, providing guidance and addressing difficulties as they arose. The IBL approach was particularly evident in the project-creation phase, when students formulated their own questions related to Molecular Biology and attempted to address them through programming in Scratch. Upon completion, projects were presented to peers, stimulating discussion and knowledge exchange. A similar structure was used in Python lessons: short theoretical explanations were followed by coding challenges that required students to implement specific commands, and the outcomes were discussed collectively.
In contrast to IBL, which was consistently embedded in lessons, gamification was employed selectively to consolidate learning after activities. Gamified sessions served as review exercises, including Kahoot quizzes on programming concepts such as indentation and variables.
Report on the course implementation
The course involved approximately 15 students aged 14–17. All enrolled participants completed the program. According to the school's academic calendar, the course was organized into three stages, although the methodology can be adapted to different teaching contexts, such as a semester-based structure with Scratch followed by Python. In the first class, a diagnostic questionnaire revealed that students had no prior programming experience, prompting adjustments to the time allocated to computational logic, Scratch, and Python based on student progress. The full schedule is presented in Supplementary Table S1.
After the theoretical introduction, students were introduced to the Scratch platform, learning to navigate its interface and use eight categories of code blocks (Motion, Looks, Sound, Events, Control, Sensing, Operators, and Variables) across eight 50-min sessions. Each lesson combined theoretical explanations with practical challenges involving sprite behavior. During this stage, Inquiry-Based Learning (IBL) was applied, encouraging students to explore and experiment with code blocks. Although all challenges were completed, increasing task complexity required more time, particularly in lessons involving variables, reflecting students' limited prior knowledge of computational logic.
To conclude the first term, students developed two Scratch games. The first, Cheese Chase (Supplementary Figure S2), was a structured maze game designed to reinforce Scratch mechanics. The second required students to create an original Scratch game or simulation illustrating Molecular Biology concepts, such as DNA transcription or protein synthesis. The Cheese Chase project involved navigating a mouse through a maze while avoiding obstacles, with sprite algorithms developed over eight lessons. Although students managed scripts for movement and collision detection, they struggled with variables, lists, and conditional statements, which led to two additional review lessons. After this reinforcement, students were able to complete the project independently.
The Cheese Chase project played a key role in identifying programming logic issues and consolidating multiple code blocks, preparing students for more complex interdisciplinary tasks. Prior to the final Scratch projects, a review lesson on Molecular Biology was conducted to address heterogeneous knowledge levels and ensure a shared understanding of DNA transcription and translation, in alignment with BNCC learning objectives. Subsequently, students worked in groups to design and implement algorithms for games focused on Molecular Biology themes (Supplementary Figure S3), promoting interdisciplinary integration and collaborative problem-solving.
The projects included question-and-answer games on DNA transcription (Supplementary Figures S3A, B), a transcription simulation (Supplementary Figure S3C), and an interactive model of cellular responses to tissue damage, illustrating genotype–phenotype relationships (Supplementary Figure S3D). These projects required fewer lessons than Cheese Chase, being completed in four 50-min classes, indicating that prior experience with a familiar game and algorithm development facilitated student progress.
Final projects were submitted for evaluation and presented in class, with the assessment focused on project development rather than theoretical testing. This approach aimed to reduce pressure, encourage creativity, and value the construction of individual knowledge. A gamified review was also conducted to reinforce Scratch concepts, as detailed in the Supplementary material. To conclude this stage, students created posters describing their projects and presented them to the school community, simulating an academic experience and fostering engagement, recognition, and interest in programming and bioinformatics among peers.
The Python project
After approximately two-thirds of the academic year working with Scratch, students began Python lessons. Programming classes with Python present a new challenge, as students will transition from a visual block-based interface to text-based programming. To support this transition, introductory theoretical content was presented, including a review of core programming concepts, text editing tools, and the advantages of Python. As school computers did not allow software installation, students used Google Colab to write and execute scripts online.
Thirteen 50-min lessons were dedicated to Python instruction. Initial classes focused on script organization, basic commands, and mathematical operators, a task facilitated by their prior experience with operator blocks in Scratch. Subsequently, students learned about variables, syntax, and data types. A gamified Kahoot review activity was used to reinforce learning, as described in Supplementary material (“Variable Types: Python”).
Conditional statements (if, elif, else) were introduced over three lessons, combining theory and practice. Students solved challenges to identify even and odd numbers and to compare DNA sequences, with minimal difficulty because they had previously used control blocks in Scratch. Looping structures (while, for, range, break, and continue) were then introduced, along with counters and indentation review. Despite their complexity, we observed that students adapted well because they were similar to Scratch blocks. Before addressing string and list manipulation, students learned about functions and methods. These skills were applied in two Molecular Biology challenges: DNA transcription to mRNA and counting cytosine and guanine bases, which introduced Chargaff's rules and reinforced the link between biology and computation.
This stage showed positive signs, as most students completed the proposed activities. The observations suggest that introducing Scratch before Python may support the development of computational thinking, as structural similarities between the two environments appear to facilitate a gradual progression toward more advanced programming concepts.
Challenges and lessons learned
Implementing an interdisciplinary bioinformatics curriculum in a high school context posed several pedagogical, technical, and organizational challenges. Throughout the 9-month program, continuous adjustments were required to align instructional strategies with students' cognitive development, prior knowledge, and institutional constraints. This experience generated valuable insights into the effective use of visual and text-based programming languages, the sequencing of instructional content, and the integration of active learning methodologies. Moreover, it led to the development of practical guidelines outlining recommended practices and common pitfalls for educators seeking to implement similar initiatives.
What to do, and what to avoid, when developing with Scratch
To facilitate the reproduction of the curriculum in other schools, we developed Table 1, which presents five key “DOs” and “DON'Ts” recommendations based on our observations and experiences throughout the teaching process. It is important to highlight that the teaching process in Scratch needs to be well-established before introducing Python. Although both languages share similar logical structures, Python introduces a more complex syntax, and students benefit from first becoming comfortable with core programming concepts in a visual, block-based environment.
What to do, and what to avoid, when developing with Scratch: a brief summary.
Do
Don't
Choose the right methodology: The chosen methodology is key to the success of the curriculum. Strategically taught content promotes a more dynamic learning experience. The use of IBL and gamification methods was fundamental, as IBL sparked students' curiosity, and gamification reinforced content through competition.
Do not let students select their own group members: While students formed their own groups and completed the scripts satisfactorily, it is important for the teacher to identify those who excel in programming logic and Molecular Biology during the introductory classes. This allows for strategically forming groups that pair students with different skill levels for better results.
Use a game previously known to the students: The selection of the game “Cheese Chase,” which was widely known, was crucial for student engagement, as they felt challenged to develop a program they had played before.
Do not wait for students to ask questions: Teaching programming in basic education is challenging, so the teacher must constantly check on students' activities. While the chosen methodology promotes autonomy, more in-depth guidance from the teacher is needed.
Dedicate a lesson to developing each sprite's script: For each sprite used in the “Cheese Chase” game, a slide was created with the rules and guidelines for each character. Each lesson focused on coding one sprite, allowing all groups to work simultaneously, providing greater support.
Do not ignore student needs: Given the novelty of teaching programming combined with Molecular Biology, there will be challenges in the learning process. Listening to students' difficulties and revisiting content is crucial to keeping them motivated.
Review Molecular Biology content: The new teaching format allows students to choose their formative path subjects, resulting in students from different grades attending the same class. This review phase was important for leveling the content across groups.
Do not skip steps: The development of the curriculum requires care and patience. After reviewing the Molecular Biology content, two introductory lessons should be scheduled: one for the group to create and submit their idea to the teacher, and another for developing the algorithm, followed by the final scripting phase.
Divide them into groups: Allowing students to form groups of up to three was a good strategy, as they could share knowledge with each other, facilitating joint learning.
Do not keep student projects unpublished: Students feel valued and motivated when their projects are shared. Moreover, showcasing their work can inspire other students to engage with the content and take the course.
To facilitate the reproduction of the curriculum in other schools, we elaborate five “DOs” and “DON'Ts recommendations throughout the teaching process based on our perspective.
What to do, and what to avoid, when developing with Python
The last stage of the elective course involved teaching Python. Complementing the findings from the Scratch lessons, it was also possible to identify different views on what to do and what not to do in the classroom. It is important to note that, in Table 2, which contains this summary, the importance of using IBL and gamification methodologies was not included; however, given the success in the course's classes, these methodologies were applied. Although the gamified activities were similar, to implement the inquiry-based method, it was necessary to provide slides containing the theoretical content covered in class for students to search, since Python code is not provided as blocks, as in Scratch.
What to do, and what to avoid, when developing with Python: a brief summary to facilitate the reproduction of the curriculum in other schools.
Do
Don't
Teach commands first in Scratch before moving on to Python: Learning programming logic is not so trivial and requires a simpler, visually appealing language, due to the color segmentation of blocks and the possibility of immediate visualization after project creation, along with a reduction in the possibility of writing errors, since commands are pre-written and divided into blocks that can be connected by students.
Do not rush through content to meet pre-established lesson plan expectations: While it is good practice to follow the planned content for each lesson, it is natural for delays to occur due to questions that arise during the process. Each class has its own difficulties and strengths, and for the successful application of this elective, it is important that no step is skipped.
Dedicate the first Python class to script organization: The selection of the game “Cheese Chase,” which was widely known, was crucial for student engagement, as they felt challenged to develop a program they had played before.
Do not conduct activities exclusively in groups: Although group activities allow for knowledge exchange, it is preferable that command explanations are individual, while exercises are done in groups.
Make correlations between learnings: Relate the commands learned in Python with the blocks present in Scratch—identifying similarities will facilitate the teaching-learning process.
Do not just verbally relate Scratch to Python: If you're using a visual resource to explain content, such as slides, add images of the command taught in Python with its corresponding block in Scratch. This will also stimulate your students' visual memory.
Use an online platform: Using Google Colab allows the notebooks containing the created scripts to be automatically synchronized in the student's own cloud, preventing loss of work and also enabling the sharing of completed activities.
Do not forget to request access to the created notebooks: Sharing the developed scripts among group members and between the group and the teacher is essential for evaluating the progress of the proposed activities. Even if the teacher sees it in class, it is important to have the file saved to track the evolution of the groups and even enable future publications and content dissemination at school events.
Use biological examples as exercises: To consolidate the given content, use Molecular Biology concepts, such as the DNA transcription process, using list manipulation. As the computational logic part is already well-established due to the previously learned language, the student will be able to create a script and, from it, understand the more abstract theoretical content by visualizing the program on their computer screen.
Do not forget to include simpler exercises: Although some students develop quickly, it is important to provide exercises compatible with the class as a whole. After solving these, you can delve deeper into the command with more elaborate exercises, such as those involving Molecular Biology.
We provide five “DOs” and “DON'Ts” recommendations throughout the teaching process from our perspective.
Future perspectives for bioinformatics in secondary education
The positive results observed in this pilot initiative highlight the potential of bioinformatics as a transformative component of secondary education. Future efforts should focus on expanding and adapting this model to different educational contexts, especially in public education systems. Establishing institutional partnerships among universities, schools, and other educational bodies can facilitate large-scale implementation and contribute to the pedagogical sustainability of these initiatives.
A critical factor for long-term success is the ongoing training of teachers with interdisciplinary knowledge. Furthermore, the development of educational platforms focused on bioinformatics, as well as the construction of databases with questions, exercises, and teaching materials, can facilitate the adoption of the curriculum by teachers with different levels of experience.
From an educational research perspective, future studies should prioritize the systematic evaluation of learning outcomes and medium- and long-term impacts. These investigations must be conducted with proper ethics committee approval, ensuring scientific integrity and the protection of participants. The data obtained will be fundamental to supporting evidence-based educational policies and the continuous improvement of proposed pedagogical models.
Finally, the consolidation of a large-scale technological curriculum depends heavily on government support. Ensuring that students from schools with limited resources have access to adequate infrastructure, teacher training, and quality educational materials is essential to prevent the deepening of digital and educational inequalities. In this sense, public investment and targeted policy formulation will be decisive for democratizing access to bioinformatics education.
Conclusion
The teaching of Molecular Biology and Bioinformatics was effective when combined with the use of programming languages: Scratch and Python. Beginning with a visually intuitive language like Scratch, which provides immediate graphical feedback, facilitates the development of computational thinking in an accessible and engaging manner. Once the foundational learning is consolidated, introducing a programming language aligned with current professional practices, such as Python, helps bring students closer to higher education and the job market.
This teaching sequence is particularly valuable, since Scratch introduces students to core programming logic through interaction with command blocks similar to those used in Python, easing the learning curve and making Python easier to learn. Moreover, concepts are more easily taught to students through active methodologies, such as gamification and inquiry-based learning, which significantly enhance student motivation and engagement. These approaches not only make abstract content more tangible but also foster deeper, more meaningful integration of biological and computational knowledge.
As a future perspective, we highlight the importance of replicating the steps described in this article to visualize the methodology in different contexts and evaluate its feasibility. Also, different approaches could be experimented with, such as integrating programming skills into Biology, Mathematics, and other disciplines. This can be an advancement toward an effective pathway to teach theoretical lessons by turning students into their own creators of knowledge.
Author's note
An earlier version of this work was presented at the 17th Brazilian Symposium on Bioinformatics (Vitória, Brazil, 2024).
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants' legal guardians/next of kin in accordance with the national legislation and the institutional requirements.
The authors thank the funding agencies: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Also, the authors thank the Laboratory of Bioinformatics and Systems and the Colégio Nossa Senhora do Monte Calvário teams.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2026.1666709/full#supplementary-material
Gamification Class - Scratch: Example of a use of the gamification methodology on the “Program's Coding” class – https://create.kahoot.it/share/gamification-class-scratch/4d97e0b3-1278-4283-bc9d-3d724bd48918
Variable Types - Python: Example of a use of the gamification methodology on the “Program's Coding” class – https://create.kahoot.it/share/variable-types-python/fe940019-9c25-421c-bf25-89a50de40a7e
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Edited by: Marcelo Reis, State University of Campinas, Brazil
Reviewed by: Michael J. Wolyniak, Hampden–Sydney College, United States
Jennifer Drew, University of Florida, United States