Psychometrics of MOOCs: Measuring Learners’ Proficiency

Abstract

Massive open online courses (MOOCs) are "one of the most significant technological developments in higher education in the past decade" (Deng, Benckendorff, & Gannaway, 2019, p. 48). MOOCs are large scale web-based courses developed by universities, solely or in cooperation with industrial partners (for example, Coursera, 2015), in which anyone with internet access can participate. MOOCs are published on provider platforms, for instance, Coursera, edX, XuetangX, FutureLearn, Udacity, MiriadaX. MOOCs are a relatively new instructional form -the term did not exist before 2008 (Major & Blackmon, 2016). However, their popularity grows fast -over a decade more than 800 universities offered to learners more than 9,400 MOOCs (Shah,

Human touch in digital education—a solution

“…Since online learning has become such a staple in today's pandemic situation, the emphasis may be shifted from content and design of the course to support, guidance and feedback from instructors and peers in a group learning approach as furthered by cMOOCs. Psychometric modelling may analyse learner proficiency, motivation and personality type to derive an algorithm-driven personalised understanding of the suggested courses to improve the likelihood of course completion rates [10].…”

Probabity distributions of the academic performance of online courses's students as a tool for assesment of the quality of control materials

“…Это свидетельствует о повышенной сложности материалов итогового теста или недостаточной подготовленности слушателей к его прохождению, после завершения текущих занятий. Наконец, предлагаемый вариант оценки, по мнению авторов, может быть использован в качестве полезного дополнения к широко распространенным при оценке заданий онлайн курсов психометрическими методами [12].…”