Index

Decision-Based Learning: An Innovative Pedagogy that Unpacks Expert Knowledge for the Novice Learner

ISBN: 978-1-80043-203-1, eISBN: 978-1-80043-202-4

Publication date: 16 September 2021

This content is currently only available as a PDF

Citation

(2021), "Index", Wentworth, N., Plummer, K.J. and Swan, R.H. (Ed.) Decision-Based Learning: An Innovative Pedagogy that Unpacks Expert Knowledge for the Novice Learner, Emerald Publishing Limited, Leeds, pp. 173-177. https://doi.org/10.1108/978-1-80043-202-420211018

Publisher

:

Emerald Publishing Limited

Copyright © 2021 Emerald Publishing Limited


INDEX

Accreditation Board for Engineering and Technology (ABET)
, 58

Activity diagram
, 74

Adaptive expertise
, 4

Advanced Writing
, 135

American Library Association (ALA)
, 119

Analysis of variance (ANOVA)
, 39

Analytical conditional knowledge
, 119, 150

Anxiety
, 26

Apprentice
, 2

Assessment
, 7, 17, 105

Assignments
, 17, 64, 79, 85, 152

Association of College and Research Libraries (ACRL)
, 119

Bloom’s Revised Taxonomy
, 23

Bomb calorimeter
, 34

Book of Mormon (BOM)
, 111

Brave place for learning
, 95

Brigham Young University’s Center for Teaching and Learning (BYU CTL)
, 94, 96

Brigham Young University’s library (BYU library)
, 124

Canvas
, 26

Center for teaching and learning (CTL)
, 154

Chemistry
, 32–33

Classification tree
, 58

Coaching
, 8, 29

COAST framework
, 32

Composition branch
, 52

Comprehension
, 32

Concept maps
, 12, 23

Conceptual knowledge
, 2–3, 5, 48–49, 150

Conditional knowledge
, 2–5, 17, 33, 48, 94, 121, 149–150

into courses
, 40–41

within IL domain
, 134–135

impacts novice to expert knowledge of discipline
, 33

of scriptural text
, 103–105

Conditional schema
, 4–7

Confidence interval estimation
, 13

Confirmatory factor analysis (CFA)
, 83

Coulomb’s law
, 49–50

Course design
, 114

course purpose and culminating assessment activity
, 57–58

creating EDM
, 58–60

for DBL
, 57

DBL problem creation
, 61–63

learning modules
, 60–61

Course EDM
, 137–139

Critical thinking
, 74

Data-driven decision-making (DDDM)
, 94, 96

Decision model
, 58–59

Decision path
, 17

Decision point
, 13

Decision-based learning (DBL)
, 1–2, 12–17, 23, 32, 46, 68, 93, 105–106, 118, 121–122, 148

assessment after implementing DBL software
, 113–114

course design for
, 57–63

creating problems in DBL software tool
, 73–77

creating problems to use in DBL software tool
, 36–37, 139–141

as design method
, 5–7

developmental progression of expertise
, 2–5

in engineering context
, 56–57

experience in engineering course
, 65

frequent, interleaved assessment
, 7

high scaffolding, problem-based interaction
, 8

in IL instruction
, 135–136

implementation of DBL IL session
, 143–144

implementing DBL into course
, 37, 40–41, 63–65, 107–109

pedagogy
, 56–57

self-directed, variable-scaffolding practice
, 7–8

software
, 109–113

as teaching method
, 7–8

Developmental progression of expertise
, 2–5

Diagraming
, 69

Educational Inquiry, Measurement & Evaluation (EIME)
, 25, 28

Engineering

course design for DBL
, 57–63

DBL experience in engineering course
, 65

decision-based learning in engineering context
, 56–57

implementing DBL into course
, 63–65

problems
, 60

theory
, 56–57

Enthalpy
, 36

Evaluate
, 5

Evaluative conditional knowledge
, 119, 150

Execute
, 23–24

Expert
, 2–3

expert-blind spot
, 3–5, 35, 149

thinking
, 160–162

Expert decision model (EDM)
, 5–6, 12, 15, 34–36, 46–47, 57, 81, 94, 107–108, 137, 148

building
, 50–51

changes
, 51–53

composition branch
, 52

creating
, 58–60

creating and implementing
, 122–127

details of
, 70–73

determining
, 69–70

developing
, 150–155

framing initial DBL question
, 47–50

implementing
, 156–159

multiple regression
, 83–84

physical properties
, 52–53

SEM
, 84

in statistics course
, 25

Fake news
, 117

Feedback
, 14, 24

First-year college chemistry
, 46

First-year Writing (FYW)
, 118

Flipped classroom
, 135–136

Formative learning using DBL
, 88

Functional expertise
, 4

General chemistry decision model, initial decision point in
, 49–50

Generative expertise
, 4

Grade Point Average (GPA)
, 39

Growth mindset
, 95

Guidance
, 29

Guidelines for Assessment and Instruction in Statistics Education (GAISE)
, 81

Heat
, 36

Hess’s law
, 36–37

Heuristics
, 32–33

Historical context
, 105–106

Homework
, 26–27, 29

Hypothesis test
, 13

Implement
, 23–24

Inductive learning
, 104

InfoGraphics
, 155

Information literacy (IL)
, 119, 133

conditional knowledge within IL domain
, 134–135

decision-based learning in IL instruction
, 135–136

evaluating student learning
, 145

implementation of DBL IL session
, 143–144

method of IL instruction
, 135

redesigning IL session
, 136–142

Information seeking
, 139

Information systems

creating problems in DBL software tool
, 73–77

details of expert decision model
, 70–73

determining expert decision model
, 69–70

redesigning course purpose
, 68–69

and Systems Analysis and Design course
, 67–68

Informed creativity
, 14

Instructor

impacts on
, 144

implementation experience for
, 63–64

Introductory religion course

conditional knowledge of scriptural text
, 103–105

redesigning course
, 105–114

research and possibilities
, 114–115

Intuition
, 20

Journeyman
, 2

Just-enough
, 6, 13, 155

Just-in-time instruction
, 6, 13, 155

Just-in-time teaching (JiTT)
, 81

Knowledge, 2–3 (see also Learning)

base and value system
, 127

dimension
, 23

domains
, 47

levels of expertise
, 4

relationship of levels to
, 3

Learning (see also Decision-based learning (DBL))

model
, 39

modules
, 60–61, 141–142

outcome
, 5

statistics
, 80

Learning management system (LMS)
, 110

Library days
, 124

Library instruction sessions
, 120–121

Machine Design
, 57

Master
, 2

Mechanical engineering
, 153

Mini-models
, 34–35, 76, 151, 154–155

Model development process
, 34–36

Modeling decisions
, 134

Modified Mohr failure theory
, 63

Mplus
, 83–84

Multiple regression
, 81

challenges for instructors
, 86

challenges for students
, 86–87

comparison of learning to students in past
, 89–90

comparison of learning to students not in DBL sections
, 91

creating problems to use with decision-based learning tool
, 84–85

EDMs
, 83–84

formative learning using DBL
, 88

redesigning courses
, 82

summative learning using DBL
, 89

Narrative research
, 148

Non-conservative failure theory
, 63

Novice

teachers
, 20

thinking
, 160–162

Objectives
, 20, 57

One-sample t-test for means
, 13

One-shot library instruction
, 120–121

One-shot methods
, 120

One-way analysis of variance
, 39

Pedagogy
, 5, 12, 150

Pilot testing
, 143

Problem bank
, 7, 57, 61, 139–140

Problem solving
, 32–33

Procedural expertise
, 4

Procedural knowledge
, 2–3

Process knowledge
, 48

Process skills
, 48

Project
, 69

Project Information Literacy (PIL)
, 119

Qualitative research
, 94

DBL
, 96

implementation of EDM
, 97–99

results
, 100–101

shift to teaching qualitative methods
, 96–97

Quasi-experimental design
, 124

Rapid mental processing
, 20, 160

Religious education
, 103–104

Repetition
, 21, 23

Research evaluation
, 94

Safe space
, 95

Scaffold
, 7–8, 53

Scenario building
, 143

Schema building
, 111

Schemized knowledge
, 94

Science, technology, engineering, and mathematics (STEM)
, 32

Scriptural text
, 103–105

Scripture
, 104

Semesters
, 143–144

Source evaluation
, 118

behaviors
, 128–130

creating and implementing expert decision model
, 122–127

current modules
, 130–131

literature review
, 120–122

results
, 128–130

Statistical Package for the Social Sciences (SPSS)
, 26, 82

statistics
, 80

anxiety
, 22–23

education
, 80

Stats 2
, 82

Structural equation modeling (SEM)
, 81

challenges for instructors
, 86

challenges for students
, 87–88

comparison of learning to students in past
, 89–90

comparison of learning to students not in DBL sections
, 91

creating problems to use with decision-based learning tool
, 85–86

EDMs
, 84

formative learning using DBL
, 88–89

redesigning courses
, 82–83

summative learning using DBL
, 89

Student learning
, 94, 161–162

challenges
, 37–38

conditional knowledge
, 33, 40–41

conditional knowledge impacts novice to expert knowledge of discipline
, 33

decision model for acid–base chemistry
, 42

evaluating
, 145

evaluating
, 39–40

perceptions/challenges for students
, 38–39

problem solving and heuristics
, 32–33

redesigning course
, 34–37

statistics
, 80

Students

comments
, 162–164

engagement
, 145

impacts on
, 144

implementation experience for
, 64

knowledge
, 136

Summative learning using DBL
, 89

Systems Analysis and Design course
, 67–69

Systems analyst
, 69

Teaching assistant (TA)
, 75

Teaching statistics
, 21–22

Time frame
, 143

Tukey post-hoc analysis
, 39

Understanding
, 3, 165

Web-based software
, 64

Well-populated, conditionally organized problem or scenario bank
, 6–7

Writing Program Administrators (WPA)
, 118–119

YSearch
, 124–125