Education in the Information Era

1. Education in the Information Era Improving Educational Interactions through Digital Media

2. Tell me and I forget, Teach me and I may remember, Involve me and I learn. – Ancient Chinese proverb (Xunzi)

3. Background • Postsecondary education can be seen to fulfill two primary roles: • To provide educational services to students • To develop human capital for the benefit of society and economy • Advances in computing and communications technology have allowed for interactive, on-demand services for obtaining and distributing information which are largely integrated into students’ daily lives • Despite this technical progress and the growing expectations by students for engaging instruction, postsecondary institutions continue to deliver content primarily through transmissive, non-interactive means • The integration of digital media offers the potential to increase student engagement, performance, and knowledge retention, thus better meeting the expectations of students and providing for more effective development of human capital

4. Interaction Model • Postsecondary institutions are built largely around the teacher-content-student set of interactions: • Educators produce content to instruct students • Students respond to select content to provide evidence of their learning • Social interactions (SS, ST, and TT) are important, but not typically part of the formal educational process • Digital media allows for significant enrichment at the content interface Source: Emergence and Innovation in Digital Learning (Veletsianos, 2016)

5. SCI: Digital Enrichment • Online content repositories allow for student access irrespective of temporal and geographical constraints, widening access but in many cases adopting the constraints inherent in non-digital educational practices • Digital platforms permit the temporal integration of instruction, assessment, and feedback • Khan Academy and Duolingo are two online learning platforms which demonstrate the feasibility and efficacy of this approach • Computer-based visualization techniques and interactive models are useful tools in conceptualization and understanding • Unique to the digital environment, content can be changed dynamically in response to student inputs to provide personalized instruction

6. Personalization through Evolutionary Tuning • Content was selected for students according to three parameters: • Learning style • Perceived complexity of learning objects • Learning interactivity • Evolutionary algorithm used to tune the compatibility of learning objects with respect to these parameters • Improvement in minimum, maximum, and average scores after tuning • Significant increase in student satisfaction with learning process after tuning Source: Christudas, Kirubakaran, and Thangaiah (in press)

7. TCI: Learning Analytics • The wealth of data, both explicit and implicit, provided by students in online environments can offer insight into the efficacy of specific pedagogical practices • Learning analytics is “the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environment in which it occurs” • Data from learning analytics can be manually interpreted and visualized through software to provide instructors with information regarding the efficacy of their instructional approach • Machine-learning algorithms can be developed to operate directly on these data, without instructor intervention, to modify the instructional environment to meet student needs

8. TCI: Assessment Practices • Traditional evaluation of student learning relies on a small number of summative assessments, conducted under pressure and divorced from applicable contexts • Formative assessment, easily conducted through a digital platform, provides educators with feedback on student performance and comprehension during the learning process • Stealth assessment allows for a continuous account of student progress and performance through analysis of learning analytics

9. Nontechnical Barriers to Digital Integration • Despite technological maturity, there exist a number of non-technical issues which bear on the feasibility of digital integration in formal education: • Due to their size, organizational complexity, and funding modalities, public educational institutions exhibit a cultural inertia which limit their response time in adopting emergent technologies • The relative cost of designing, implementing, and maintaining flexible digital learning technologies requires efficiencies gained through economies of scale • Any institutional use of learning analytics requires strict adherence to ethical practices regarding informed consent, data privacy, and deidentification • Digitally-integrated assessment practices pose problems in verifying student identity