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Doctoral seminar2016

Esimene esitlus doktoritöö teemadel

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Doctoral seminar2016

  1. 1. Research Seminar 02.11.2016 Reference Architecture for Data Collection and Analytics in Smart Schoolhouse Marge Kusmin
  2. 2. Motivation ❖ A Paradigm Shift in Education ❖ Estonian Lifelong Learning Strategy 2020 ❖ change in the approach to learning ❖ Digital Turns towards 1:1 computing ❖ Transition to new socio-technical regime in schools requires consensus on a new architecture for educational services (cloud-based, BYOD-focused, service-oriented, intelligent, interoperability) 2
  3. 3. Background ❖ In recent decades, there has been a lot of changes in the way technology is used in teaching and learning process: from simple content delivery on multimedia CDs to complex enterprise-level online learning systems (Moodle, EIS, eKool) ❖ BYOD, cloud-based services and IoT are pushing us towards another “digital turn” in schools: “smart schoolhouse” ❖ The potential of IoT (linking physical and virtual worlds) in teaching and learning context has not been yet systemically researched, coherent “big picture” is missing ❖ Reference architecture might be one potential solution 3
  4. 4. What is reference architecture? ❖ A Reference Architecture provides a template solution for particular software architectures in a specific domain ❖ RA provides a common vocabulary with which to discuss implementations, define software requirements, quality indicators etc. ❖ Example of Reference Architecture for SOA -> 4
  5. 5. Research problem ❖ How to describe to different stakeholders the core aspects of the hardware and software architecture for “smart schoolhouse” that enables automatic data collection from physical learning environment so that this data could be integrated with the digital footprints of learners (in their BYOD and online platforms) and then used for learning analytics purposes? 5
  6. 6. Research question (1) ❖ Which technology to select for data collection from the physical learning environment? ❖ What kind of data can be (and has been) collected in the classrooms with available sensor/IoT technologies? ❖ What kind of data should never be collected from the school premises? ❖ Which sensors/IoT technologies are optimal to introduce in the “smart schoolhouse” context? 6
  7. 7. Research question (2) ❖ What are the components and structure for Reference Architecture of the smart schoolhouse (RASS)? ❖ What are the common patterns of existing sensor/IoT hardware and software setups in school settings? ❖ How to visualise the RASS? ❖ What are expectations of various stakeholders while applying RASS in different contexts (e.g. hardware procurements, network setup, learning analytics)? 7
  8. 8. Research question (3) ❖ How to validate, implement and develop RASS? ❖ Which existing validation approach is optimal for RASS and how it needs to be adapted? ❖ How to manage the life cycle of RASS? ❖ How to make RASS meaningful and useful for different stakeholders? 8
  9. 9. Methodology ❖ Mixed methods research design following the emerging agile and iterative design-based research that implemented in three cycles: ❖ Analysis phase: review of related research and available sensor/IoT technologies for “smart schoolhouse”; focus group interviews with experts and teachers ❖ Design phase: setting up a pilot “smart classroom” in TLU HIK, small-scale empirical data collection and co-design of RA with TLU students and school pupils ❖ Implementation phase: Re-designing and implementing the RA on setting up “smart classroom” in Väätsa Põhikool, a school-level data collection 9
  10. 10. Expected outcomes of the study ❖ To design a Reference Architecture for data-rich physical and virtual learning environment by combining large amount of automatically generated data from various sources (teachers computer, BYOD, online learning environment) environmental sensors installed in the classroom (air, light, movement, infrared etc.) and wearable sensors gathering bio- and neurofeedback from students and teachers to detect patterns that help analyse students’ reactions and emotions during their study process. 10
  11. 11. Tentative time Schedule ❖ I semester - literature review ❖ II semester - setting up a pilot classroom in HIK ❖ III, IV semester - suggestions to and setting up an experimental study ❖ V, VI semester - the experimental study and data collection in real-life settings in one pilot school ❖ VII semester - analysing, validating, comparing the data ❖ VIII semester - finishing the thesis 11
  12. 12. Discussion ❖ Use of sensors/IoT in other contexts: ❖ SmartHouse, SmartHome, SmartBuilding ❖ air quality, temperature, noise, light, glow, humidity, chair occupancy ❖ SmartCity ❖ presence, location/position, proximity, gesture ❖ SmartHealth ❖ skin and body temperature, heart rate, respiratory rate, blood pressure, emotional stress, eye tracking/eye gaze ❖ What els? 12
  13. 13. Research Seminar 02.11.2016 Thanks!