PowerPoint
Thinking with educational data
Ming-Chi Liu ()
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(Affective learning)
[email protected]
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This is an exciting time to be a statistician (Horton &
Hardin, 2015).Statistician frequently ranks as a top job
(Wasserstein 2015).
Our curricula need to prepare students engage in the entire data
analysis process (Horton & Hardin, 2015).7
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ASA Guidelines for Programs in Statistical ScienceIncreased
importance of data science
Real applications
More diverse models and approaches
Ability to communicate8(ASA, Nov. 2014)
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cs109.org
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Data is the New Everything
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http://www.slideshare.net/condamoor/next-generation-analytics-architecture-for-business-advantage
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http://www.slideshare.net/AmandaMakulec/identifying-your-audience-40086476
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PISA PISA (the Programme for International Student
Assessment)
PISA 2012 65 51 15
16PISA 2012 results in focus: What 15-year-olds know and what
they can do with what they know. (2014). Retrieved from
www.oecd.org/pisa
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What Makes Schools Successful? Resources, Policies and
Practice17
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Allocation of educational resources and mathematics
performance
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Teachers' salaries and mathematics performance
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PISA?
21https://www.ted.com/talks/andreas_schleicher_use_data_to_build_better_schools/
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22http://sa.ylib.com/MagCont.aspx?Unit=featurearticles&id=2096
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2020500()
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(Stats
Monkey)24http://singularityhub.com/2009/11/09/is-software-set-to-replace-sports-journalists/
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https://en.wikipedia.org/wiki/Infinite_monkey_theorem
201626http://www.wired.com/2009/04/newtonai/http://www.wired.com/2009/12/download-robot-scientist/
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http://krishna.org/evolution-from-scientist-to-monkey/
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Sorbonne University:
""28https://share.inside.com.tw/posts/16864
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29http://www.nytimes.com/roomfordebate/2016/03/09/does-alphago-mean-artificial-intelligence-is-the-real-deal/the-skills-of-human-interaction-will-become-most-valuable-in-the-future
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???
Think with data30
2016Motivated Strategies Finder31Liu, Ming-Chi, & Wu,
Ting-Ting. (Under review). Strategies Finder: Assess motivated
strategies from teaching opinion by using aspects based sentiment
analysis. IEEE Transactions on Learning Technologies.
Motivational processes monitoring10.04.17.12.21.25.19.28.14.
2016Possible data sources: Time-consumingLog, : Passive,
High/Low
Assess motivated strategies from teaching opinion32
201633Label Propagation12710.83Sentiment analysis6860.77
=> => => => 1 => -1
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34Liu, Chia-Ju, Huang, Chin-Fei, Liu, Ming-Chi, Chien, Yu-Cheng,
Lai, Chia-Hung, & Huang, Yueh-Min*. (2015). Does gender
influence emotions resulting from positive applause feedback in
self-assessment testing? Evidence from neuroscience. Educational
Technology & Society, 18(1), 337-350.
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Positive applause feedback in self-assessment testingRewarding
with applause sound during computerized test
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Two tests36
the controlled task
the experimental task30 students (15 males, 15 females; mean age
S.D. = 19.2 2.0 years) participated in this experiment.
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Timeline of experimental procedure37
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Gender differences in anxiety38
The controlled task
The experimental task
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Applause decrease males anxiety39
Topographical map of the brain
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In-class questions
40Huang, Yueh-Min, Liu, Ming-Chi, Lai, Chia-Hung, & Liu,
Chia-Ju. (In Press). Using humorous images to lighten the learning
experience through questioning in class. British Journal of
Educational Technology. doi:10.1111/bjet.12459
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Research methodology41Study1Study2Study3Number of
participants442923Lecture typesVideo lecturesClassroom
lecturesClassroom lecturesCourse contentsFinancial literacyData
structureComputer networksExperimental
methodsBetween-groupWithin-groupWithin-grouptreatmentsImage
rewarded in-class questionsImage rewarded in-class questionsImage
rewarded in-class questionsInstruments AffectionFacial expression,
EEGLearning confidenceLearning
confidenceCognitionPre-/Post-knowledge testsPost-knowledge
testPost-knowledge tests
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RewardClick the correct answer
Reap the image reward
2016Flow chart of applying funny image rewards to in-class
questions 43
2016The timeline of the research design44week 3week 5week 7week
4week 6week 8week 9week 1week 2
15 min.LectureIn-class questions without reward15 min.15 min.15
min.
Short answer questions (comprehension & confidence)15
min.
15 min.LectureIn-class questions with image reward15 min.15
min.15 min.
Short answer questions (comprehension & confidence)15
min.
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45The trend-lines for level of learning confidence in the two
courses from weeks three to eight
The data structure courseThe computer network courseNot
rewardedRewardedANOVACoursesMSDMSDdfFdData structure
(n=29)1.750.852.240.95287.59**.21Computer network
(n=23)1.800.512.400.752220.75***.49
**p < .01. ***p < .001.The maximum score is 3A
repeated-measures one-way ANOVA for students' level of learning
confidence between rewarded and no rewarded classes in two
courses
201646Not rewardedRewardedIndependent
t-testCoursesMSDMSDdftdData structure
(n=29)4.792.265.451.8256-1.215.32Computer network
(n=23)6.222.518.302.2044-3.064**.89
Independent t-test for students' mean test scores for questions
receiving and without receiving rewards in two courses
2016The importance of Group Reward
Students expressed their intention to help their peers learn the
course materials for seeing a funny image.
Sears and Pai (2012) demonstrate that group reward will promote
greater knowledge sharing and group cohesiveness.47
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Online Synchronous Learning environment
48Lai, Chia-Hung, Liu, Ming-Chi, Liu, Chia-Ju, & Huang,
Yueh-Min. (2016). Using positive visual stimuli to lighten the
online synchronous learning experience through in-class
questioning. International Review of Research in Open and Distance
Learning, 17(1), 23-41. doi:10.19173/irrodl.v17i1.2114
2016Experiment environment49
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The average degree of negative valence of the participants
receiving images/not receiving images within five seconds of
answering each question.
201651VariableNPre-testPost-testANCOVAMeanSDMeanSDF(1,
39)dWithout funny picture2124.0515.7880.9512.711.4950.37With funny
picture2126.9012.6085.4710.11
Pre- and posttest mean scores, standard deviations, and analysis
of covariance (ANCOVA) results for two group
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52, , , , & . (2015, May 22-23). . Paper presented at the ,
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2016(Social presence theory)
: (Rovai, 2007)
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(community reflection)
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(community reflection)
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?1. Think with data 2. Frame your problem59
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Excel
slideshare
Liu, Ming-Chi, & Huang, Yueh-Min. (In Press). The use of
data science for education: The case of social-emotional learning.
Smart Learning Environments. 60
201661Thank You for ListeningEmail: [email protected]
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2010 - Yisell.com
