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