An Interactive Assessment Framework for Visual Engagement: Statistical Analysis of a TEDx Video

This study aims to assess the visual engagement of the video lectures. This analysis can be useful for the presenter and student to find out the overall visual attention of the videos. For this purpose, a new algorithm and data collection module are developed. Videos can be transformed into a dataset with the help of data collection module. The dataset is prepared by extracting the image frames from the video and marking them with a number of faces, the number of eyes, the status of eyes and the engagement score along with nominal values of engagement level. This data is transformed into time-based data items by using the attribute number of frames processed per second (PFPS). A case study for the assessment of TEDx video (length 8 minutes and 53 seconds) is included to validate the results and to extract statistical information from the dataset. Frames in the video are 16047 and they are transformed into 2675 keyframes. Machine learning classifiers are applied for the analysis of the dataset. The findings of this analysis help the presenter and the student to measure the quality of the visual content of the videos without actually going through it.

[1]  Stephen Reysen,et al.  Video lecture format, student technological efficacy, and social presence in online courses , 2012, Comput. Hum. Behav..

[2]  Hasan Karal,et al.  Application of Graph Theory in an Intelligent Tutoring System for Solving Mathematical Word Problems , 2016 .

[3]  René F. Kizilcec,et al.  Showing face in video instruction: effects on information retention, visual attention, and affect , 2014, CHI.

[4]  R. Vanderlinde,et al.  Evaluating ICT Integration in Turkish K-12 Schools through Teachers' Views. , 2016 .

[5]  Janice Witt Smith,et al.  Video Lecture Capture Pedagogy Context: Does it matter and does it Deliver? , 2014 .

[6]  Chia-Ming Chang,et al.  Verification of Social Network Site Use Behavior of the University Physical Education Students , 2016 .

[7]  Dave Paul Meade,et al.  The Evolution of an Electronic Assessment for Evaluating Trip Risk, Compliance, Approval Level and Tracking , 2012 .

[8]  Paul F. Newbury,et al.  The effects of video lecture delivery formats on student engagement , 2015, 2015 Science and Information Conference (SAI).

[9]  Matthew P. Buman,et al.  Rural Food and Physical Activity Assessment Using an Electronic Tablet-Based Application, New York, 2013–2014 , 2015, Preventing chronic disease.

[10]  Patrick Jermann,et al.  Your click decides your fate: Inferring Information Processing and Attrition Behavior from MOOC Video Clickstream Interactions , 2014, Proceedings of the EMNLP 2014 Workshop on Analysis of Large Scale Social Interaction in MOOCs.

[11]  Jacob Bishop,et al.  Testing the flipped classroom with model-eliciting activities and video lectures in a mid-level undergraduate engineering course , 2013, 2013 IEEE Frontiers in Education Conference (FIE).

[12]  Andreas Prokop,et al.  A Novel Electronic Assessment Strategy to Support Applied Drosophila Genetics Training in University Courses , 2015, G3: Genes, Genomes, Genetics.

[13]  Michail N. Giannakos,et al.  Usability design for video lectures , 2013, EuroITV.

[14]  Chih-Ming Chen,et al.  Effects of Different Video Lecture Types on Sustained Attention, Emotion, Cognitive Load, and Learning Performance , 2015, IIAI-AAI.

[15]  Jamshid Ghajar,et al.  Assessing Attention: Relationship between Circular Visual-Tracking and Spatial Span, and Implication for Electronic Assessment , 2015 .

[16]  Ramazan Yirci,et al.  Turkish Adaptation of the Mentorship Effectiveness Scale: A Validity and Reliability Study. , 2016 .

[17]  Eileen Nicolle,et al.  Using TED Talks to teach social determinants of health: maximize the message with a modern medium. , 2014, Canadian family physician Medecin de famille canadien.

[18]  Marcello Federico,et al.  Report on the 10th IWSLT evaluation campaign , 2013, IWSLT.