Using Custom-Built, Small-Scale Educational Solutions to Teach Qualitative Research Literacy: No Code, Code, and Complex Applications

Using Custom-Built, Small-Scale Educational Solutions to Teach Qualitative Research Literacy: No Code, Code, and Complex Applications

Geraldine Bengsch
DOI: 10.4018/978-1-7998-7271-9.ch046
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Abstract

This chapter considers ways in which educators can create their own educational applications to integrate into their teaching. It is argued that interactive uses of technology can aid student engagement and encourage uptake of skills presented to them. Today, tools available allow everyone to create not only static websites, but also functional applications. It is possible to get started without knowing how to code, empowering anyone with an interest in technology to become a creator. While these no and low code solutions may come with some restrictions, they may encourage users to explore more traditional ways to engage with code and its possibilities for teaching. The chapter aims to encourage readers to look at technology as a creative practice to include into their teaching. It suggests strategies to help readers select the most appropriate tool for their projects.
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Introduction

This chapter describes the potential for interactive, custom-built solutions in higher education in teaching qualitative research methods. Gamification has been of increased interest for increasing student engagement and motivation (Aldemir, Celik, & Kaplan, 2018; Tan & Hew, 2016; Tsay, Kofinas, & Luo, 2018). However, gamification does not solely rely on features such as rewards and badges, but rather aims to create an environment that stimulates learning and the acquisition of competencies (Torres-Toukoumidis, Rodríguez, & Rodríguez, 2018; Yıldırım & Şen, 2019). In this sense, the aim is to create multimodal learning experiences that support student learning and competence in conducting research. Learning and teaching can be personal, practice-based and integrated to fit students as digital citizens (Keppell, 2014). Societies are changing and reveal mismatches between education and work reality (Azivov, Atamuratova, Holova, Kamalova, Akobiova, & Oltiev, 2020). This also affects pedagogical models and how they are applied in the classroom (Carvalho &Yeoman, 2018). However, the incorporation of technology may be limited to repetitive activities, such as reading from the screen or ticking boxes, calling for more creative applications of resources available (Kirschner, 2005). The chapter illustrates how applications can be constructed using a variety of tools. It shows examples of basic to more advanced applications to use in qualitative research method courses, constructed with no code and code-based tools. The chapter uses several example applications the author created to discuss considerations when creating custom-built teaching tools.

Key Terms in this Chapter

No Code: Software development approach that requires non to little programming skills. Some services allow to convert familiar formats, such as Google Sheets (“sheet2site”), into a functionable website without writing any code.

Graphical User Interface (GUI): A form of user interface using graphical icons and menus.

JavaScript (JS): A high-level scripting language used to add interactivity to a web page. Allows to dynamically update content, interact with content, animate images, or control media.

Deployment: Software deployment. Activities that make software available to use on a device. Low and no code environments often have integrated deployment solutions. Other free services include Netlify and Heroku.

Low Code: Development platform or environment that allows the creation of applications through a graphical user interface, allowing for a visual approach to software development. Adobe Dreamweaver combines a GUI with writing actual code in a simplified manner. Thunkable, for example, uses drag-and-drop to create mobile apps using code chanks.

Machine Learning: Computer algorithms which improve through the use of data, without following explicit instructions. Part of artificial intelligence.

What You See Is What You Get (WYSIWYG): Editor that displays the document exactly as it would appear in the finished product. Original examples include word processing software such as Microsoft word, and code editors, such as Adobe Dreamweaver.

Learning Management System (LMS): Software application for educational, training and development courses. Allows for administration, tracking and documentation of courses. Examples include BlackBoard and Moodle.

HTML and CSS: “hypertext markup language” and “cascading style sheets” are core technologies in building web pages. HTML is the standard markup language to display text in browsers that defines the structure of a site. CSS is a style sheet language that describes the presentation of a web site.

Topic Model: A type of statistical model in machine learning to uncover abstract themes in a collection of texts.

Integrated Development Environment (IDE): A software environment with comprehensive facilities for software development, including source code editor, build automation tools and debugger. Examples include Visual Studio Code, PyCharm, and Sublime Text.

Application (App): Computer or software application. A computer program to carry out a specific task for a specific purpose. Designed for an end user.

Application Programming Interface (API): A software service that allows two programmes to transmit data between each other. Allows to access other company’s data or software to enhance functionality and features in another app without having to create it from scratch.

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