Abstract
Although it is widely recognized that exam and assessments are ways to explore and query knowledge, emergence of the internet, digitalization, and the deployment of artificial intelligence in teaching and learning extends the concept to digital exam and assessment. Some lines of research suggest that digital exam and assessments are costly and unfortunate, whereas others suggest that it is beneficial and adaptive. However, there are little theoretical underpinnings probing these arguments. To fill the void, this chapter probe existing teaching and learning literature, and concepts of digital exam and assessments relative to faculty development. To this end, this chapter theorize that these concepts are contingents on generational cohorts, arguments that advances and reorients research on digital exam and assessment, and generational difference are highlighted. The chapter concludes with pros and cons associated with digital assessments.
TopIntroduction
The traditional classification of assessment tends to divide students’ work into two categories: formative and summative. A summative exam is one that individuals take to demonstrate the possession of knowledge and capability in a given area or subject and sometimes to obtain a diploma or certificate. Formative assessment tends to count for a smaller percentage in grading and often results in a larger amount of feedback, whereas, summative assessment focuses on an outcome, for instance, final exam scores or grades. However, all assessment serves as ‘an engine for learning.’
Scholars argue that institutions see online courses as a long-term strategy due to the ability to improve teaching and provide access to a wide range of audiences (Allen & Seaman, 2015). The adoption of online courses has led to increasing use of computer-mediated assessment in both summative and formative areas (Bälter, Enström, & Klingenberg, 2013). To avoid computer-mediated assessment from being perceived as a fad, administrators and educators need to rethink online pedagogy to utilize this type of assessment to demonstrate meaningful learning (Gikandi, Morrow, & Davis, 2011).
The majority of the modern Learning Management Systems (LMS) and Virtual Learning Environments (VLE) incorporate online tests, gamification, assessment functionalities, instant and deferred feedback for both distance and hybrid learning courses. Digital assessments permit both students and instructors to evaluate progress and failure.
The percentage of U.S. students taking at least one online course has increased steadily from 25.9% in 2002 to 31.6% in 2016 (Seaman, Allen, & Seaman, 2018; Soffer, Kahan, & Livne, 2017; Toven-Lindsey, Rhoads, & Lozano, 2015). However, the learning quality and learning outcomes of online courses compared to face-to-face, traditional courses continue to be the subject of vigorous debate in the academe (Jaschik & Lederman, 2018). In view of this steady increase of online learning adoption in tertiary institutions and the conflicting attitudes toward overall quality, assessment of these courses is essential and critical both for faculty and students (Stödberg, 2012; Soffer, Kahan, & Livne, 2017). Online learning assessment entails the evaluation of online learning effectiveness, its impacts, and outcomes (Angus & Watson, 2009). In addition, understanding students’ motivation and the barriers with regard to online learning is important to tailor personalized learning (Soffer, Kahan, & Livne, 2017). Online learning platforms enable tracking, assessing, and responding to student behavior with far greater depth and speed compared to the traditional approach (Prineas & Cini, 2011).
Key Terms in this Chapter
Generational Cohorts: This is the classification of individuals with shared historical experiences spanning from schooling, employment, retirements, national and international to several other developmental stages. These series of events are the key determinants of individual’s attitudes, behaviors and values in one’s social life. Generational cohorts are classified as Boomers, Gen-Xers, Gen-Yers, and Gen-Zers.
Artificial Intelligence (AI): AI applies machine learning, deep learning, and predictive analytics to provide teaching and learning solutions. AI ideation proffers that machines can execute tasks smartly (i.e., to “think” like a human and mimic the way a person acts) through learning and adaptation by experience.
Digital Exam and Assessments: It is the use of the Internet and its applications to evaluate students’ cognitive ability and performance. It involves accessing personalized education, examination materials and feedback anytime and anywhere, all of which are said to make it more efficient than the traditional assessment.
T-Shaped Skills: They describe specific attributes of desirable students. The vertical bar of the T refers to students’ skills and knowledge in a particular subject, while the top of the T refers to the ability to collaborate with other students and a willingness to use the skills and knowledge gained from this collaboration.
Industry 4.0: Named also as the fourth industrial revolution, which focuses on the establishment of intelligent faculty development practices, teaching and learning processes. It entails automation and data exchange in cyber-physical systems e.g., the Internet of things, digitalization, artificial intelligence, cloud, and cognitive computing.