%0 Book Section %1 Schmitz2017 %A Schmitz, Marcel %A van Limbeek, Evelien %A Greller, Wolfgang %A Sloep, Peter %A Drachsler, Hendrik %B Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estonia, September 12--15, 2017, Proceedings %C Cham %D 2017 %E Lavoué, Élise %E Drachsler, Hendrik %E Verbert, Katrien %E Broisin, Julien %E Pérez-Sanagustín, Mar %I Springer International Publishing %K dashboard feedback learninganalytics learningdesign metacognition reflection %P 209--223 %R 10.1007/978-3-319-66610-5_16 %T Opportunities and Challenges in Using Learning Analytics in Learning Design %U https://doi.org/10.1007/978-3-319-66610-5_16 %X Educational institutions are designing, creating and evaluating courses to optimize learning outcomes for highly diverse student populations. Yet, most of the delivery is still monitored retrospectively with summative evaluation forms. Therefore, improvements to the course design are only implemented at the very end of a course, thus missing to benefit the current cohort. Teachers find it difficult to interpret and plan interventions just-in-time. In this context, Learning Analytics (LA) data streams gathered from `authentic' student learning activities, may provide new opportunities to receive valuable information on the students' learning behaviors and could be utilized to adjust the learning design already ``on the fly'' during runtime. We presume that Learning Analytics applied within Learning Design (LD) and presented in a learning dashboard provide opportunities that can lead to more personalized learning experiences, if implemented thoughtfully. %@ 978-3-319-66610-5

@inbook{Schmitz2017, abstract = {Educational institutions are designing, creating and evaluating courses to optimize learning outcomes for highly diverse student populations. Yet, most of the delivery is still monitored retrospectively with summative evaluation forms. Therefore, improvements to the course design are only implemented at the very end of a course, thus missing to benefit the current cohort. Teachers find it difficult to interpret and plan interventions just-in-time. In this context, Learning Analytics (LA) data streams gathered from `authentic' student learning activities, may provide new opportunities to receive valuable information on the students' learning behaviors and could be utilized to adjust the learning design already ``on the fly'' during runtime. We presume that Learning Analytics applied within Learning Design (LD) and presented in a learning dashboard provide opportunities that can lead to more personalized learning experiences, if implemented thoughtfully.}, added-at = {2017-09-25T22:37:24.000+0200}, address = {Cham}, author = {Schmitz, Marcel and van Limbeek, Evelien and Greller, Wolfgang and Sloep, Peter and Drachsler, Hendrik}, biburl = {https://www.bibsonomy.org/bibtex/2f0638c2883bab5b442305e1cd5c2260d/ereidt}, booktitle = {Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estonia, September 12--15, 2017, Proceedings}, doi = {10.1007/978-3-319-66610-5_16}, editor = {Lavou{\'e}, {\'E}lise and Drachsler, Hendrik and Verbert, Katrien and Broisin, Julien and P{\'e}rez-Sanagust{\'i}n, Mar}, interhash = {3f3768f0df4b2c26f8388cf34ccdd34f}, intrahash = {f0638c2883bab5b442305e1cd5c2260d}, isbn = {978-3-319-66610-5}, keywords = {dashboard feedback learninganalytics learningdesign metacognition reflection}, pages = {209--223}, publisher = {Springer International Publishing}, timestamp = {2017-09-25T22:37:24.000+0200}, title = {Opportunities and Challenges in Using Learning Analytics in Learning Design}, url = {https://doi.org/10.1007/978-3-319-66610-5_16}, year = 2017 }