Teaching with digital biology

Opportunities from authentic sequences and 3D models

Abstract

Background: Swiss schools are required to develop students’ digital competencies in each discipline (CIIP, 2018). However, teachers in Geneva, Switzerland aren’t supplied with many official resources or recommendations to help them implement these requirements. This article presents a project that developed a theoretical framework referring to three types of digital education skills (DES): (DES A) new approaches to building or validating knowledge, (DES B) critical-thinking skills, (DES C) new didactic methods and elaborated proposals to help biology teachers comply with the requirements. Building and discussing models is a core scientific practice and can develop understanding of scientific phenomena and the nature of disciplinary knowledge (Schwarz et al., 2009). The digitisation of biology and affordable 3D printers make it possible to produce tangible models of most proteins mentioned in secondary biology education from freely available, authentic research data. This combination opens unprecedented opportunities for classroom activities, allowing students to (DES A) practice digital biology methods based on a discussion of solid evidence (DES A) and (DES B) support the development of critical thinking.

Purpose: This article first presents a theoretical perspective developed to reveal the learning potential of digital biology, focuses on its feasibility, and finally discusses the educational potential offered by scenarios, with some data from a proof-of-principle example. Based on how biology research nowadays builds knowledge and on research showing educational benefits of using authentic research data and 3D models (better questions, more discussion of models, enhancing motivation), this article presents technical step-based course-of-action scenarios (CoAscenarios) that were tested in classrooms, helping teachers and learners to access and use authentic data to address difficult learning issues such as evolution or the form–function problem, by manipulating authentic research data and physical, tangible mod-els. With a focus on strengthening students’ skills in building and validating knowledge using the new digital approaches (DES A), the CoAscenarios contribute to the ongoing change process rather than pedagogical guidelines, which come from educational authorities. They are designed to be used independently of teachers’ methods. This article seeks to stimulate discussion of these opportunities and the challenges that many schools face.

Sample/setting: In a proof-of-principle example, we describe one possible use of selected CoAscenarios (Nos. 17, 20, 21) tested in three pilot classes in upper secondary school (N = 48 students in total, 2016-2019) and improved in over 20 in-service teacher training courses (since 2002). These activities, including hypothesis testing and discussions of data as evidence of evolution, are organised in the format of a classical hands-on school lab.

Design and Methods: The project (2019-2021) collected 25 classroom-tested CoAscenarios which are now presented on an open MediaWiki platform. As a proof-of-principle, we discuss three CoAscenarios: No. 17 concerning sequence data, and No. 20 and No. 21 concerning tangible models. In CoAscenario 17, students used authentic protein sequences to compare the degree of similarity of one protein each across different species, visualised as highlights on aligned sequences, and discussed this evidence of common origin and of divergence caused by mutations. Then, students observed areas of their protein sequence in which little or no change could be observed across species. They discussed how natural selection can explain this evidence. Using 3D-printed tangible models, they compared conserved parts of the sequence with areas of the model to test and improve their naïve mental models with regards to the learning goals. To this effect, teachers used CoAscenario 20, in which a table gives the protein name, a link to its sequence, biological information in the UniprotKB database, 3D structures in the Protein Data Base (PDB), a picture of the 3D-printed model, and ready-to-print files (.STL). CoAscenario 21 helps teachers convert 3D structures from the PDB to a 3D-printable format. Feedback about feasibility and usefulness was collected in questionnaires. This led to improvements being made to the platform. Data from student questionnaires were analysed for perceptions of these learning activities. We will also briefly present some results from a questionnaire used in a teacher training course.

Observations: Results from classroom observations: the students handled technical steps with more ease than ex-pected, allowing discussions to focus on biological questions such as natural selection, mutation, how proteins fold, protein–substrate interactions, conservation of structures in evolution, how specific areas of the protein determine function and, in some cases, the limits of the lock-and-key model.

Conclusions: Results confirm the feasibility of such approaches and their alignment with the educational reforms of the discipline. Our results suggest that the choice made in the project to propose CoAscenarios expressed as technical steps frees the teacher to focus the lesson design on biological concepts, activities and discussion of the evidence found, rather than on the technical mastery of websites and platforms. Expected difficulties, such as drawing from different models for explanations, were confirmed. The use of authentic research data helped reveal conceptual gaps in student understanding and allowed teacher feedback that guided students towards better mental models. This should help dissemination at this early stage of adoption of digital biology. Results also open new educational strategies based on authentic data embodied in material objects and databases and suggest more research into the educational effects of 3D model use in different learning designs.

Keywords: Models, evolution, 3D structure, bioinformatics, learning designs, authentic data, digital learning