Educational Stakeholders’ Independent Evaluation of an Artificial Intelligence-Enabled Adaptive Learning System Using Bayesian Network Predictive Simulations

Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a...

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Published in:Education sciences Vol. 9; no. 2; pp. 110 - 141
Main Authors: HOW, Meng-Leong, HUNG, Wei Loong David
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.06.2019
Subjects:
Adaptive learning
Artificial Intelligence
Bayesian
Bayesian analysis
Bayesian Statistics
Cognition & reasoning
Cognitive ability
Control Groups
Education policy
Educational Environment
Educational Policy
Educational technology
Evaluation Methods
evaluation of artificial intelligence educational systems
Hypotheses
Hypothesis Testing
intelligent adaptive learning
Intelligent Tutoring Systems
Interactive learning
Mathematical problems
Mathematics education
Mathematics teachers
nonparametric data
Nonparametric statistics
Pedagogy
Prediction
Pretests Posttests
Probability
Problem Solving
Researchers
Simulation
Stakeholders
Students
Teaching
Teaching Methods
United States > US
Germany
Singapore
ISSN:2227-7102, 2227-7102
Online Access:Get full text
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Abstract Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved for large-scale deployment. Beyond simply believing in the information provided by the AI-ALS supplier, there arises a need for educational stakeholders to independently understand the motif of the pedagogical characteristics that underlie the AI-ALS. Laudable efforts were made by researchers to engender frameworks for the evaluation of AI-ALS. Nevertheless, those highly technical techniques often require advanced mathematical knowledge or computer programming skills. There remains a dearth in the extant literature for a more intuitive way for educational stakeholders—rather than computer scientists—to carry out the independent evaluation of an AI-ALS to understand how it could provide opportunities to educe the problem-solving abilities of the students so that they can successfully learn the subject matter. This paper proffers an approach for educational stakeholders to employ Bayesian networks to simulate predictive hypothetical scenarios with controllable parameters to better inform them about the suitability of the AI-ALS for the students.
AbstractList Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved for large-scale deployment. Beyond simply believing in the information provided by the AI-ALS supplier, there arises a need for educational stakeholders to independently understand the motif of the pedagogical characteristics that underlie the AI-ALS. Laudable efforts were made by researchers to engender frameworks for the evaluation of AI-ALS. Nevertheless, those highly technical techniques often require advanced mathematical knowledge or computer programming skills. There remains a dearth in the extant literature for a more intuitive way for educational stakeholders--rather than computer scientists--to carry out the independent evaluation of an AI-ALS to understand how it could provide opportunities to educe the problem-solving abilities of the students so that they can successfully learn the subject matter. This paper proffers an approach for educational stakeholders to employ Bayesian networks to simulate predictive hypothetical scenarios with controllable parameters to better inform them about the suitability of the AI-ALS for the students.
Author HOW, Meng-Leong
HUNG, Wei Loong David
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Cites_doi 10.1007/978-3-7091-2670-7_24
10.1101/lm.041780.116
10.1007/978-3-319-07221-0_18
10.1108/IJILT-09-2016-0040
10.1016/0004-3702(86)90072-X
10.1111/j.1467-8535.2009.01042.x
10.1080/00461520.2011.611369
10.1177/0049124114562614
10.1201/b10391
10.1109/18.910572
10.1098/rstl.1763.0044
10.1111/cdev.12169
10.1093/oxfordhb/9780199796304.013.0033
10.1080/00220973.2016.1277338
10.1007/BF01126111
10.1037/a0026802
10.1007/3-540-68716-5_49
10.3390/educ2010022
10.1038/nrn3475
10.3389/fnhum.2011.00039
10.1016/j.cherd.2011.12.012
10.1177/0165025407077764
10.1109/TIT.1953.1188572
10.1111/j.2517-6161.1988.tb01721.x
10.1111/bjep.12157
10.1080/00461520.2016.1207540
10.1145/956804.956838
10.1016/j.jspi.2008.10.002
10.1007/3-540-61327-7_156
10.5539/ies.v11n2p97
10.1017/CBO9780511803161
10.1177/0165025407077763
10.1111/1467-8535.00347
10.1207/s15327906mbr3904_4
10.1080/0266476042000184019
10.1177/1365480215616313
10.1007/978-3-642-14363-2
10.1186/s40536-016-0022-6
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References Mathys (ref_23) 2011; 5
Egalite (ref_46) 2016; 19
Kaplan (ref_21) 2016; 4
Shannon (ref_27) 1953; 1
Bekele (ref_25) 2011; 42
ref_36
ref_13
ref_35
Guoyi (ref_32) 2012; 90
Button (ref_17) 2013; 14
Pezzulo (ref_43) 2016; 23
Zhang (ref_20) 2007; 31
ref_31
ref_30
Lauritzen (ref_41) 1988; 50
Lee (ref_16) 2004; 39
Brusilovsky (ref_9) 2004; 14
ref_18
Fox (ref_33) 2009; 139
ref_39
Kschischang (ref_42) 2001; 47
Chamberlin (ref_45) 2017; 87
Levy (ref_22) 2016; 51
ref_37
Pearl (ref_15) 1986; 29
Garrido (ref_3) 2012; 2
VanLehn (ref_6) 2006; 16
Wilson (ref_1) 2017; 34
Hox (ref_10) 2012; 6
ref_47
Peterson (ref_34) 2004; 31
Boyer (ref_7) 2014; Volume 8474
Mantzicopoulos (ref_48) 2018; 86
Walker (ref_19) 2007; 31
Agosta (ref_26) 2002; 32
Jameson (ref_38) 1996; 5
ref_40
ref_2
ref_29
ref_28
Fateel (ref_44) 2018; 11
Asparouhov (ref_24) 2012; 17
Cen (ref_5) 2007; 158
Kaplan (ref_12) 2014; 85
VanLehn (ref_4) 2011; 46
Bayes (ref_11) 1763; 53
Magoulas (ref_8) 2003; 34
Pearl (ref_14) 2015; 44
References_xml – ident: ref_28
– ident: ref_37
  doi: 10.1007/978-3-7091-2670-7_24
– volume: 23
  start-page: 322
  year: 2016
  ident: ref_43
  article-title: Active inference, epistemic value, and vicarious trial and error
  publication-title: Learn. Mem.
  doi: 10.1101/lm.041780.116
– volume: Volume 8474
  start-page: 150
  year: 2014
  ident: ref_7
  article-title: Learning Bayesian Knowledge Tracing Parameters with a Knowledge Heuristic and Empirical Probabilities
  publication-title: Intelligent Tutoring Systems
  doi: 10.1007/978-3-319-07221-0_18
– volume: 16
  start-page: 227
  year: 2006
  ident: ref_6
  article-title: The behavior of tutoring systems
  publication-title: Int. J. Artif. Intell. Educ.
– volume: 32
  start-page: 171
  year: 2002
  ident: ref_26
  article-title: Pérez de la Bayesian student modeling and the problem of parameter specification
  publication-title: Br. J. Educ. Technol.
– volume: 34
  start-page: 2
  year: 2017
  ident: ref_1
  article-title: Adaptive systems in education: A review and conceptual unification
  publication-title: Int. J. Inf. Learn. Technol.
  doi: 10.1108/IJILT-09-2016-0040
– volume: 29
  start-page: 241
  year: 1986
  ident: ref_15
  article-title: Fusion, propagation, and structuring in belief networks
  publication-title: Artif. Intell.
  doi: 10.1016/0004-3702(86)90072-X
– volume: 42
  start-page: 395
  year: 2011
  ident: ref_25
  article-title: A Bayesian performance prediction model for mathematics education: A prototypical approach for effective group composition
  publication-title: Br. J. Educ. Technol.
  doi: 10.1111/j.1467-8535.2009.01042.x
– volume: 46
  start-page: 197
  year: 2011
  ident: ref_4
  article-title: The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems
  publication-title: Educ. Psychol.
  doi: 10.1080/00461520.2011.611369
– volume: 44
  start-page: 149
  year: 2015
  ident: ref_14
  article-title: Causes of Effects and Effects of Causes
  publication-title: Sociol. Methods Res.
  doi: 10.1177/0049124114562614
– ident: ref_30
  doi: 10.1201/b10391
– volume: 14
  start-page: 402
  year: 2004
  ident: ref_9
  article-title: Layered evaluation of adaptive learning systems
  publication-title: Int. J. Contin. Eng. Educ. Lifelong Learn.
– volume: 47
  start-page: 498
  year: 2001
  ident: ref_42
  article-title: Factor graphs and the sum product algorithm
  publication-title: IEEE Trans. Inf. Theory
  doi: 10.1109/18.910572
– ident: ref_40
– volume: 53
  start-page: 269
  year: 1763
  ident: ref_11
  article-title: A Letter from the Late Reverend Mr. Thomas Bayes, F.R.S. to John Canton, M.A. and F. R. S
  publication-title: R. Soc. Philos. Trans.
  doi: 10.1098/rstl.1763.0044
– volume: 85
  start-page: 842
  year: 2014
  ident: ref_12
  article-title: A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research
  publication-title: Child Dev.
  doi: 10.1111/cdev.12169
– ident: ref_18
– ident: ref_35
– ident: ref_47
  doi: 10.1093/oxfordhb/9780199796304.013.0033
– volume: 86
  start-page: 214
  year: 2018
  ident: ref_48
  article-title: Predicting Kindergarteners’ Achievement and Motivation from Observational Measures of Teaching Effectiveness
  publication-title: J. Exp. Educ.
  doi: 10.1080/00220973.2016.1277338
– volume: 5
  start-page: 193
  year: 1996
  ident: ref_38
  article-title: Numerical uncertainty management in user and student modeling: An overview of systems and issues
  publication-title: User Modeling User-Adapt. Interact.
  doi: 10.1007/BF01126111
– volume: 17
  start-page: 313
  year: 2012
  ident: ref_24
  article-title: Bayesian structural equation modeling: A more flexible representation of substantive theory
  publication-title: Psychol. Methods
  doi: 10.1037/a0026802
– ident: ref_39
  doi: 10.1007/3-540-68716-5_49
– volume: 2
  start-page: 22
  year: 2012
  ident: ref_3
  article-title: AI and Mathematical Education
  publication-title: Educ. Sci.
  doi: 10.3390/educ2010022
– volume: 14
  start-page: 365
  year: 2013
  ident: ref_17
  article-title: Power failure: Why small sample size undermines the reliability of neuroscience
  publication-title: Nat. Rev. Neurosci.
  doi: 10.1038/nrn3475
– volume: 5
  start-page: 39
  year: 2011
  ident: ref_23
  article-title: A Bayesian foundation for individual learning under uncertainty
  publication-title: Front. Hum. Neurosci.
  doi: 10.3389/fnhum.2011.00039
– volume: 90
  start-page: 1235
  year: 2012
  ident: ref_32
  article-title: Response surface methodology with prediction uncertainty: A multi-objective optimisation approach
  publication-title: Chem. Eng. Res. Des.
  doi: 10.1016/j.cherd.2011.12.012
– volume: 31
  start-page: 374
  year: 2007
  ident: ref_20
  article-title: Bayesian analysis of longitudinal data using growth curve models
  publication-title: Int. J. Behav. Dev.
  doi: 10.1177/0165025407077764
– ident: ref_29
– volume: 158
  start-page: 511
  year: 2007
  ident: ref_5
  article-title: Is Over Practice Necessary?—Improving learning efficiency with the cognitive tutor through Educational Data Mining
  publication-title: Front. Artif. Intell. Appl.
– volume: 1
  start-page: 105
  year: 1953
  ident: ref_27
  article-title: The lattice theory of information
  publication-title: IRE Prof. Group Inf. Theory
  doi: 10.1109/TIT.1953.1188572
– volume: 50
  start-page: 157
  year: 1988
  ident: ref_41
  article-title: Local computations with probabilities on graphical structures and their application to expert systems
  publication-title: J. R. Stat. Soc.
  doi: 10.1111/j.2517-6161.1988.tb01721.x
– volume: 87
  start-page: 422
  year: 2017
  ident: ref_45
  article-title: Using confirmatory factor analysis to validate the Chamberlin affective instrument for mathematical problem solving with academically advanced students
  publication-title: Br. J. Educ. Psychol.
  doi: 10.1111/bjep.12157
– volume: 51
  start-page: 368
  year: 2016
  ident: ref_22
  article-title: Advances in Bayesian Modeling in Educational Research
  publication-title: Educ. Psychol.
  doi: 10.1080/00461520.2016.1207540
– ident: ref_31
  doi: 10.1145/956804.956838
– volume: 139
  start-page: 2498
  year: 2009
  ident: ref_33
  article-title: Bayesian credible intervals for response surface optima
  publication-title: J. Stat. Plan. Inference
  doi: 10.1016/j.jspi.2008.10.002
– ident: ref_36
  doi: 10.1007/3-540-61327-7_156
– volume: 11
  start-page: 97
  year: 2018
  ident: ref_44
  article-title: Students’ Achievement in Math and Science: How Grit and Attitudes Influence?
  publication-title: Int. Educ. Stud.
  doi: 10.5539/ies.v11n2p97
– ident: ref_13
  doi: 10.1017/CBO9780511803161
– volume: 31
  start-page: 366
  year: 2007
  ident: ref_19
  article-title: The application of Bayesian analysis to issues in developmental research
  publication-title: Int. J. Behav. Dev.
  doi: 10.1177/0165025407077763
– volume: 6
  start-page: 87
  year: 2012
  ident: ref_10
  article-title: How few countries will do? Comparative survey analysis from a Bayesian perspective
  publication-title: Surv. Res. Methods
– volume: 34
  start-page: 511
  year: 2003
  ident: ref_8
  article-title: Adaptive web-based learning: Accommodating individual differences through system’s adaptation
  publication-title: Br. J. Educ. Technol.
  doi: 10.1111/1467-8535.00347
– volume: 39
  start-page: 653
  year: 2004
  ident: ref_16
  article-title: Evaluation of the Bayesian and maximum likelihood approaches in analyzing structural equation models with small sample sizes
  publication-title: Multivar. Behav. Res.
  doi: 10.1207/s15327906mbr3904_4
– volume: 31
  start-page: 251
  year: 2004
  ident: ref_34
  article-title: A Bayesian approach for multiple response surface optimization in the presence of noise variables
  publication-title: J. Appl. Stat.
  doi: 10.1080/0266476042000184019
– volume: 19
  start-page: 27
  year: 2016
  ident: ref_46
  article-title: The softer side of learning: Measuring students’ non-cognitive skills
  publication-title: Improv. Sch.
  doi: 10.1177/1365480215616313
– ident: ref_2
  doi: 10.1007/978-3-642-14363-2
– volume: 4
  start-page: 7
  year: 2016
  ident: ref_21
  article-title: Causal inference with large-scale assessments in education from a Bayesian perspective: A review and synthesis
  publication-title: Large-Scale Assess. Educ.
  doi: 10.1186/s40536-016-0022-6
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SubjectTerms Adaptive learning
Artificial Intelligence
Bayesian
Bayesian analysis
Bayesian Statistics
Cognition & reasoning
Cognitive ability
Control Groups
Education policy
Educational Environment
Educational Policy
Educational technology
Evaluation Methods
evaluation of artificial intelligence educational systems
Hypotheses
Hypothesis Testing
intelligent adaptive learning
Intelligent Tutoring Systems
Interactive learning
Mathematical problems
Mathematics education
Mathematics teachers
nonparametric data
Nonparametric statistics
Pedagogy
Prediction
Pretests Posttests
Probability
Problem Solving
Researchers
Simulation
Stakeholders
Students
Teaching
Teaching Methods
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