BEGIN:VCALENDAR
VERSION:2.0
PRODID:Baylor CMS Calendar /PHP/
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:US_Central
BEGIN:STANDARD
DTSTART:20001029T020000
RRULE:FREQ=YEARLY;WKST=MO;INTERVAL=1;BYMONTH=11;BYDAY=1SU
TZNAME:Standard Time
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20010401T020000
RRULE:FREQ=YEARLY;WKST=MO;INTERVAL=1;BYMONTH=3;BYDAY=2SU
TZNAME:Daylight Saving Time
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:Baylor_CMS_Event-82773
DTSTAMP:20260614T062920Z
SUMMARY:Dr. Wick's Colloquium: Evaluating Distance Learning in Graduate Biostatistics Courses
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:Dr. Jo Wick (University of Kansas Medical Center): “A Bayesian Evaluation of Distance Learning in Graduate Biostatistics Courses”=0D=0A=
 =0D=0A=
Distance learning can be useful for bridging geographical barriers to education in rural settings, similar to those served by the University of Kansas Medical Center (KUMC). However, empirical evidence on the equivalence of distance education and traditional face-to-face (F2F) instruction in statistics is mixed and its interpretation is not clear. Despite the difficulties associated with performing a randomized controlled experiment for evaluating learning in different instruction environments, we have minimized the intra-instructor variation by providing courses offered in the traditional F2F setting to a separate set of students simultaneously via online learning technology.  This technology allows for two-way interaction between instructor and all students enrolled in the course, minimizing the perceived isolation of online learners resulting from a lack of face-to-face contact with the instructor. Our primary objective was to compare student performance between the two teaching modes among seven graduate-level statistics courses. We present a novel comparison using a Bayesian hierarchical model to perform a meta-analysis of equivalence. The frequentist mixed model approach was also conducted for reference. The results of Bayesian and frequentist methods agree and suggest equivalence in student performance. Finally, discussion is given to barriers to instruction and learning using the applied online teaching technology. (Questions? Email: Jane_Harvill@baylor.edu)
LOCATION:Sid Richardson, Room 208
DTSTART;TZID=US_Central:20130321T163000
DTEND;TZID=US_Central:20130321T173000
END:VEVENT
END:VCALENDAR