Flipping large lectures! Philip Walker School of Mathematics, - PowerPoint PPT Presentation

Introduction Design Results Conclusions Flipping large lectures! Philip Walker School of Mathematics, University of Leeds P.Walker@leeds.ac.uk E-assessment in the Mathematical Sciences 13 September 2016 P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions Section 1 Introduction P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions Flipped classroom Core concepts Active and passive learning Inside and outside class Feedback and discussion P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions Flipped classroom The challenge Large enrolment (ca. 160 students) Inappropriate room (raked lecture theatre) P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions MATH1400 Modelling with Differential Equations Second-order . . . P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions MATH1400 Modelling with Differential Equations Second-order . . . . . . linear . . . P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions MATH1400 Modelling with Differential Equations Second-order . . . . . . linear . . . . . . constant coefficient . . . P. J. Walker Flipping large lectures!

Introduction Design Background Results Context Conclusions MATH1400 Modelling with Differential Equations Second-order . . . . . . linear . . . . . . constant coefficient . . . . . . ordinary differential equations P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions Section 2 Design P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The ends Reducing the drag Eliminate repetitive examples from class Allow more time for interaction P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The means Structure Online Learning Unit (OLU) Quiz Notes Video P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The means Structure Online Learning Unit (OLU) Numbas Quiz Question Notes Video P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The means Structure Online Learning Unit (OLU) Numbas Quiz Question Notes Video Next OLU FAQ lecture P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The means Structure Online Learning Unit (OLU) Numbas Quiz Question Notes Video Next OLU FAQ lecture Student- Student- Student- guided interacting facing P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions The means Structure Online Learning Unit (OLU) Numbas Quiz Question Assignment Notes Video Next OLU FAQ lecture Student- Student- Student- guided interacting facing P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Section 3 Results P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Data sources Online survey in OLU 3 ( n = 74) Socrative exit tickets Assessment data ( n = 157) P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Experience The students In hours, how long did the OLUs take you? Data Best fit Gamma distribution 0 5 10 15 µ = 5 . 75 ± 0 . 74 hr (95% CI) P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Experience The students Do you agree or disagree with the following statements? Meeting the learning objectives Time well spent Stimulating learning experience Doing more work Agree Disagree Would like more of this style of learning More engaged than traditional methods Less learning support Less effective than traditional methods P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Experience The students Pro Con Work at own pace ( × 3) Deadline: not at own pace Work more Work more ( × 4) Understand more Good examples ( × 4) OLUs vs assignment OLUs a struggle FAQ lectures ( × 2) FAQ lectures ( × 3) Quizzes: self-diagnosis Strong, general positive ( × 2) Self-directed learning Didn’t answer all questions Too difficult P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Experience The lecturer Pro Con Better feedback from students Upfront cost of work Improvement in rapport More interesting teaching P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Data analysis Class segmentation Group the class by number of OLUs completed: OLUs Engagement n 0 None 22 1 Partial 16 2 Partial 26 3 Full 93 P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Data analysis Mean performance on each exam question by segment 15 10 Exam E1 E2 E3 E4 5 0 None Partial Full P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Data analysis Mean performance on each exam question by segment 15 10 Exam E1 E2 E3 E4 5 0 None Partial Full P. J. Walker Flipping large lectures!

Introduction Data sources Design Experience Results Performance Conclusions Data analysis Segment scores on assignments 1.00 Engagement Full 0.75 Partial None 0.50 0.25 0.00 0 5 10 15 20 P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions Section 4 Conclusions P. J. Walker Flipping large lectures!

Introduction Design Results Conclusions This is worth the effort, with caveats Student (and lecturer) experience is enhanced Student performance appears unaffected A useful means of identifying disengaged students? P. J. Walker Flipping large lectures!