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
- Prelims
- Chapter 1: Why Decision-based Learning is Different
- Chapter 2: How to Use Decision-based Learning
- Chapter 3: I Am Not a Real Statistician; I Just Play One on TV
- Chapter 4: Make Thinking Explicit to Support Student Learning
- Chapter 5: Creating an Expert Decision Model Designed to Improve Student Learning in First-year General Chemistry Courses
- Chapter 6: Exploring Decision-Based Learning in an Engineering Context
- Chapter 7: Decision-Based Learning in an Information Systems Course
- Chapter 8: Decision-Based Learning in Multiple Regression and Structural Equation Modeling Courses
- Chapter 9: Using Decision-Based Learning to Teach Qualitative Research Evaluation
- Chapter 10: Implementing Decision-Based Learning in an Introductory Religion Course
- Chapter 11: Using Decision-Based Learning to Teach Source Evaluation in One-shot Library Sessions
- Chapter 12: Information Literacy and Decision-Based Learning
- Chapter 13: Lessons Learned from the Implementation of Decision-Based Learning
- References
- Index