The Design and Redesign of an Online Socio-Constructivist Course on Engineering Management: The Role of Learning Scenarios and Learning Analytics

The Design and Redesign of an Online Socio-Constructivist Course on Engineering Management: The Role of Learning Scenarios and Learning Analytics

Mary Grammatikou, Nadia Sansone, Dimitris Pantazatos, Donatella Cesareni, Vasilis Maglaris
Copyright: © 2021 |Pages: 24
DOI: 10.4018/978-1-7998-4063-3.ch003
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Abstract

This chapter focuses on the design and redesign of an online engineering management course, based on a socio-constructivist approach. At first, the theoretical and contextual premises will be presented with a focus on the suggested teaching and learning methods to acquire domain-related knowledge and crucial skills and on the importance of learning scenario to support an effective learning design. After the background introduction, a user case will be described, focusing on the course online environment and its tools, on the proposed pedagogical strategies and above all, on how instructors can obtain and analyze useful educational data from various sources. Finally, some redesign recommendations will be provided to better use educational data for continuous course improvement.
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Introduction

Engineering management is a specialized field of management concerned with the engineering sector. Reflecting industry demand for management-focused engineers, a growing number of specialized engineering management degrees are available to help develop the knowledge and skills needed for these roles. During an engineering management course, students develop industrial engineering skills, knowledge and expertise, alongside knowledge of business and management techniques, strategies and concerns. Plus, one of the main goals of higher education, whatever the domain, is to ensure that students acquire useful skills to achieve success not only in their studies but also in their future career and life in general. Through specific techniques and educational strategies, students should learn to act, study and work intentionally and effectively, individually or together with others, in authentic contexts, solving complex problems and creating new solutions and new knowledge. Based on these outcomes and core competencies, instructors should design their courses, focusing not just on the courseware, rather on the whole teaching/learning experience. Once a course is fully designed, according to the specific goals and theoretical approaches the instructor bear in mind, it comes into practice and the design process starts again.

The scope of this chapter is to examine the design and redesign of an Engineering Management course, by following some research questions:

  • Which are the core skills that a student and future worker should develop to be successful in his/her career?

  • Which teaching and learning strategies could better support the development of the identified skills?

  • Which methods a teacher should follow to design and redesign an effective course?

To answer these questions, at first, the theoretical and contextual premises will be presented, with a particular focus on the suggested teaching and learning methods suggested to acquire nowadays crucial skills. After the background introduction, we will describe our use case, with clear attention to the online environments and its tools, on the pedagogical strategies and, above all, on how instructors can obtain and analyze useful educational data from various sources, according to the Learning Analytics framework. Finally, some redesign recommendations will be provided to better use educational data for continuous course improvement.

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Theoretical Background

One of the main goals of higher education, whatever the chosen knowledge-domain, is to ensure that students acquire useful skills to achieve success not only in their studies but also in their future career and life in general (Sansone, Cesareni, Ligorio, Bortolotti & Buglass, 2019). In every age, the “useful skills” are defined according to the context in which those skills should be mobilized (Le Boterf, 1994). The context in which today's students live and work is that of a high technological impacted knowledge work society. In other words, it is a society where knowledge and technology represent two “inextricably linked” factors in any educational and professional context (Scardamalia, Bransford, Kozma, and Quellmalz, 2012, p. 234) and where uncertainty and rapidity of change are intrinsic dimensions. These features encourage the development of specific skills and consequently imply the need for educational agencies to review curricula and pedagogical practices, as also highlighted by the international community (OECD, 2013). A comprehensive list of 21st-century skills has been provided by Binkley and colleagues (2012) who identified ten skills grouped into four clusters: ways of thinking (e.g., creativity and innovation, critical thinking, problem solving, decision making, learning to learn and metacognition); ways of working (e.g., communication and collaboration – teamwork); tools for working (e.g., information literacy, ICT literacy), and living in the world (e.g., citizenship; life and career; personal & social responsibility). Equipped with these skills, tomorrow citizens should learn to act, study and work intentionally and effectively, individually or together with others, in authentic contexts, solving complex problems and creating new solutions and new knowledge. As mentioned, this means also becoming more aware of the cultural power technologies play which should not be considered merely as a content delivery mechanism, but rather as artifacts able to support human capacity for developing new culture (Engeström & Escalante, 1996; Wartfosky, 1973), therefore academic and educational contexts are called upon to develop positive, cultural models of how to use this technology.

Key Terms in this Chapter

Learning Analytics: The measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.

Learning Management System (LMS): A software application for the administration, documentation, tracking, reporting, and delivery of educational courses, training programs, or learning and development programs.

Shareable Content Object Reference Model (SCORM): A collection of standards and specifications for web-based electronic educational technology (also called e-learning).

Public License: A license by which a copyright holder as licensor can grant additional copyright permissions to all persons in the general public as licensees.

Educational Data Mining: A research field concerned with the application of data mining, machine learning and statistics to information generated from educational settings.

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