Blended Learning in a Liberal Arts Setting: Preliminary Findings

  • Published on
    10-Jul-2015

  • View
    711

  • Download
    0

Embed Size (px)

Transcript

<p>Using Blended Learning in a Liberal Arts Environment</p> <p>Studying Blended Learning in a Liberal Arts College SettingJennifer Spohrer, PhDOffice of the Provost</p> <p>1</p> <p>About the Project2Research QuestionCan a blended approach improve learning outcomes in introductory STEM courses?COMPLETIONPERSISTENCE IN MAJORENGAGEMENTMASTERY3What is Blended?Two keys to our definition:Feedback on learning outside classroom through computer-based materialsExtra-classroom learning alters how instructor teaches or uses class time</p> <p>No prescriptions beyond thisNo requirement to reduce seat timeFaculty identify pedagogical challenges and goals4Fall 2011 CoursesCourse Undergrador post-bac? Pre-requisitesIntro to major?BIOL101 Intro Bio: Molecules to CellsPBNoneNoBIOL111 Biological ExplorationsUGNoneYesCHEM101 Chemistry Fundamentals UGPlacement via pre-testPossiblyCHEM103 General Chemistry, sec. 1PB/UGPlacement via pre-test (UG)Yes (UG)CHEM103 General Chemistry, sec. 2UGPlacement via pre-testYesCMSC/LING325 Computational LinguisticsUGSome comp science or linguisticsNoECON242 Economics of Local Environmental GovernmentUGECON105NoGEOL202 Mineralogy/Crystal ChemistryUG100-level geology or chemistryYesQUAN001 Quantitative SeminarUGPlacement via pre-testNoAssessment/EvaluationIn all courses, assess perceptions of impact throughFaculty start/exit interviewsStudent attitudinal surveys</p> <p>Where possible, compare perceptions against quantifiable evidence of impactPerceived Impact: FacultyAll fall faculty intend to continue blended approach</p> <p>Why?Automatic gradingStudent learning data generated Relevance to their particular pedagogical challenges and goalsAll plan to continue to using blended approachAutomatic grading enables better assessmentBetter=more frequent=more customizedTracking data is invaluable for -- Agile teaching -- adjusting lectures and assignments on the fly-- Identifying at-risk and unengaged students-- Giving students info to ask better (more targeted, etc.) questions</p> <p>7</p> <p>Automatic gradingAssess sooner and more oftenTesting effectBuild in review</p> <p>Learning DataReal-time sense of how students are doingMore agile teachingMore fruitful conversations with students about learningRelevance to Goals/ChallengesGenerally supported pedagogical goalsLearner-centered teachingResponding to classroom diversityApproaches that encourage deep learning10ExamplesBIOL 110-113 Exploration Courses Half-semester, topic-basedFear that students wont get fundamentalsHeterogeneity of student preparation and goals</p> <p>GEOL202 Mineralogy/Crystal ChemistryIntro to major, but tedious memorization Blending produces better outcomes and frees up class time for more interesting activities</p> <p>Better than ExpectationsAttitude to computer-based learning going intocoursePrior ExperienceReported Use of MaterialsIn some cases, software generates tracking data we can compare Self-Reported Use of Materials</p> <p>OtherComplete assignmentExplore on my ownReview for testExtra practiceUnderstand lecturePrepare for lectureWhat Had Impact: StudentsImmediacy of FeedbackKnew sooner whether they had understoodAble to better structure study time</p> <p>Focus on Mastery (not their words)Made mistakes, got feedback before it countedMore practice if neededBut, just as important no busywork!Next StepsMeasure student performanceGradesStandardized assessmentsLong-term retentionCompare toHistorical data on for coursesPredicted performance (SATM, placement tests)Learning data tracked by courseware</p>

Recommended

View more >