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Using Web-Based Tools in Small Enrollment Discussion-type Classes
M.A. Wattiaux
Department of Dairy Science
22
Modeling the “Learning Space” for Life-long Learning
Lectures Independentstudies
Discussion
Background
33
Changes in The “Learning Space”
AL
L
L LL
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LL L L
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ALibrary
Black board / screen
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L L L LL L
Black board / screen
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L L L LL L
Freshmen Senior
Passive Active
Simple answers Complex answers
Learning as anindividual process
Learning is ateam process
Multi-discipline analysisDisciplinary knowledge
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L LL
LL
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A ALibraryInternet
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AProfessionals
Professor
Background
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Creating a Environment that Convinces Students that…
• Learning is not a spectator sport;
• Learning is not about finding the “ the right” answers;
• Learning is not about memorizing pre-packaged assignments;
• Learning is not following somebody else’s opinion.
• Learning comes from analyzing and evaluating evidence (data);
• Learning is both an individual and a team process;
Background
55
Creating a Environment that Convinces Instructors that…
• Teaching is not (having students enjoy) a spectator sport;
• Teaching is not about (having students) finding the “ the right” answers;
• Teaching is not about (having students) memorizing pre-packaged assignments.
• Teachjng is about motivating and empowering students
• Teaching is about helping others use knowledge for a purpose (solve problems, build certain skills, etc.)
Background
66
Who is Doing What, When and Where?
Before class After classDuring class
Instructor as a“Lecturer”
Prepare for lecture
Students… - Memorize
(Listen, take notes)
Lectures
???
Instructor as a “Designer”
- Analysis;- Discussion;- Clarification.
Students…
Prepare for Discussion
-Complete assignments;
- Connect;- Read, etc.,
Background
77
Moving the Technology OUT of the Class
Before class After classDuring class
Instructor as a“Lecturer”
Students…
CLASSROMPROJECTION
Instructor prepares Lecture
Students memorize lecture
Instructor as a “Designer”
- “Live” interaction
Students…
WEB - CD WEB - CD
Background
88
Objectives
To share lessons learned from attempts in using web-based tools to help students prepare for discussion as the primary mode of class time interaction.
Lessons learned will be drawn primarily from two courses taught to Juniors, Seniors and Graduate Students— A required “Ruminant Nutrition”— An elective “Environmental Management of Livestock Operation”
Specifically
Objective
Student Assessment of Learning Gain— Course Survey— Course Evaluation
How do we know what works? (Method)
Ruminant Nutrition (Dy Sci 414)
313 - Animal Feed and Diet FormulationCompanion to 311. Emphasis on quantitative and practical aspects of animal feeds and diet formulation (Prerequisite: 311)
Junior
Passive dependent learning
ActiveIndependentlearning
Materials & Methods
311 - Comparative Animal Nutrition(Nutrients and their source, assimilation function and requirement).Prerequisite: Biochem and/or chem.
Sophomore
Junior
414 - Ruminant NutritionIntegrates basic nutrition concepts and ration balancing skills. Emphasis on Dairy Cattle
Senior
Junior
Grad. St.
1111
RN - Course Objectives (syllabus excerpt)
• … The first objective is to learn nutritional concepts and their implications in feeding ruminants. ….. At the end of this course, students will be more familiar with current scientific understanding and their practical implications in feeding ruminants with an emphasis on the dairy cow.
• The second objective is to foster critical thinking and self-learning processes. This course is also designed to strengthen your ability to interpret and critically evaluate information (as related to ruminant nutrition). The teaching method used in this class emphasizes ACTIVE participation in reading technical articles before class and discussing them during class.
Materials & Methods
1212
RN - Class Organization (syllabus excerpt) Materials & Methods
• … reading assignments followed by class discussion of the paper. Power point presentations by the instructor will be used to clarify key concepts as needed.
• Before Class
• Download and read assignments (http://dairynutrient.wisc.edu)
• Practice quiz
• During Class
• Participate in discussion (whole class or small group)
• Questions and answers
• After Class
• Review material and practice quiz
• Prepare for next topic
1313
RN - Syllabus (Spring 2003) (syllabus excerpt)
1
2
3
4
5
6
7
8
9
10
Ruminant vs. Non Ruminants
Feed and Forage Evaluation
NRC 2001 Energy System
NRC 2001 Protein System
Dry Matter Intake
Nutritional Management of Transition Cows
Nutrition and Reproduction
Low Fiber Diets — Rumen Acidosis — Milk Fat Depression
Calf and Heifer Nutrition
Main Topics
Materials & Methods
Hypocaclemia (Milk Fever) — Ketosis — Fat Cow Syndrome — DAs
Team project included data collection and analysis of dairy cow rations with the NRC simulation software followed by a class presentation of findings.
2020
EMLO - Course Objectives (syllabus excerpt)
• … The overall goal of this course is to study ways to improve management practices of livestock operations based on a sound understanding of balance and flow of nutrients as a continuum among the soil, plant and animals that make up the biophysical resources of a farm.
• At the end of the course students will be able:
To understand environmental concerns at different scales (global, national regional, watershed, and farm scales)
To understand current policies and regulations impacting production agriculture;
• To identify and understand the major factors indicative of— and contributing to — leakage of nutrients from agricultural systems (soil, plant and animal) to the environment (air and water).
Materials & Methods
2121
EMLO - Class Organization (syllabus excerpt)
• … Our exploration of environmental management of livestock operations will involve:
Assignment of lecture material available electronically (CD / Web) http://dairynutrient.wisc.edu/archive/ (course content) and/or http://dairynutrient.wisc.edu/ (quiz)
In-class discussions of CD / web reading assignments;
Analysis of case studies and / or farm visit;
• Use of Computer software.
2222
EMLO - Syllabus (Fall 2003) (syllabus excerpt)
1
2
3
4
5
7
8
9
Global Issues, Policies, Regulations
On-farm Nutrient Management
Soil conservation and P accumulation
Crop and Crop Rotations
Livestock Nutrition in the Context of Nutrient Management
Engineering Aspects of Manure handing and Manure treatments
Real Stories” of “Real Producers”
Main Topics
Materials & Methods
Computer lab –Whole farm nutrient balances/cycling
6 Emissions from Livestock Operations (green-house gases & ammonia)
2626
AssessmentMaterials & Methods
Questionnaire was modified from the “Student Assessment of Learning Gains” (SALG)* to address:
1- the syllabus and topics
2- the extent to which various aspects of the class help the learning
3- the “gains” resulting from class activities/assignments
4- the perceptions of students needs (interests) an the extent to which the class helps meet those needs?
* http://www.wcer.wisc.edu/salgains/instructor/
• Course Survey (3rd – 4th week of the semester)
• Course Evaluation (end-of-semester)
2727
Assessment
Materials & Methods
Answers were on a (Likert-type) scale of 1 to 5 (EMLO class):1 = Not at all Strongly disagree2 = A little Slightly disagree3 = Somewhat Neutral4 = A lot Slightly agree5 = A great deal Strongly agree
Students were encouraged to comment and explain their ratings
Answers were on a modified (Likert-type) scale of 0 to 10 (RN class):
Not atAll
ALittle
Somewhat A lot
A Great deal
1 2 3 4 5 6 7 8 9 10
2929
Statistical Analysis (Distribution of Data)
Materials & Methods
Data was plotted (visual observation)
Distribution of data from 10 selected questions from each data set was analyzed with Proc UNIVARIATE of SAS (2001). Shapiro-Wilk test for Normality:
Data was declared not normally distributed if P <= 0.01 Data was declared normally distributed if P > 0.01
Data (enrollment):EMLO: 8 students (8 paired surveys and evaluations, n = 16)RN: 18 students (unpaired surveys and evaluations, n = 36)RN: 10 students (10 paired surveys and evaluations, n = 20)
3030
Statistical Analysis(Nonparametric Analysis on Ranked Data)
• Non-parametric analysis was performed on ranked scores instead of original scores because:
• Numbers are “meaningless” by themselves, but attain meaning only in an ordinal comparison.
• The probability theory of statistics based on ranks does not depend on the distribution in many cases.
• The non-parametric “Mann-Whitney” test is never too bad when compared with the two-sample t test, the usual parametric counterpart.
• If data are normally distributed so that all of the assumptions of the usual parametric tests are met, the loss of efficiency caused by using analyzing ranked data is surprisingly small (Conover, 1999).
3131
Ranking Data (e.g. Score for q1 of RN course)
UnsortedOriginalScore
41566373
3
10
OrdinalRank
12345678
36
9
SortAscending
order
12333445
10
5
RankedScore
12
6.56.5
Average444
Average
UnsortedRankedScore
6.51
4
4
3232
Statistical Analysis (Paired data)
Materials & Methods
Data (scores for 10-12 questions) from each course was analyzed in separate analysis with Proc GLM (SAS, 2001). Model was:
rSn = µ + STy + SEt + Ee
Where:rSn = ranked score (dependent variable);µ = overall mean;STs = effect of student ST (s = 1 to 8 or 1 to 10)SEt = Effect of assessment SE (t=1 to 2; survey or evaluation) Ee = Error term
Significance was declared at P < 0.10
3333
Separation of Means
• Ruminant Nutrition
• Contrast Gender: Women vs. Men
• Contrast Standing: Juniors vs. Seniors
• Contrast Standing: Undergraduates vs. Graduate stds.
• EMLO
• Contrast Standing: Undergraduates vs. Graduate stds.
3434
Statistical Analysis (Unpaired data)
Materials & Methods
Data from RN course (n=36) was analyzed in second analysis with Proc GLM (SAS, 2001). Model was:rSn = µ + SEy + Gg + Ss + G*Sgs + SE*Sys + Ee
Where:rSn = ranked scores (dependent variable);µ = overall mean;SEy = Effect of assessment SE (y=1 to 2; survey or
evaluation)Gg = Effect of the gender (g = 1 to 2; M or F)Ss = Effect of the standing (s = 1 to 3; Jr, Se., Grad.)GSgs = Interaction of the Gth gender with the Sth standingSESys = Interaction of the yth assessment with the Sth standing Ee = Error term
3636
Data Distribution“I learn a lot in this
course”
1-5 Likert-scale(EMLO)
1-10 Likert-scale(RN)
02468
1012
1 2 3 4 5 6 7 8 9 10
Score
Fre
qu
ency
(n
)
02468
1012
1 2 3 4 5
Score
Fre
qu
ency
(n
)
3737
Data Distribution Characteristics
QuestionCourse: RN (modified likert scale of 1 to 10; n = 36)
1 2 7 12 19 20 22 25 26 28 29 43
Mean 5.8 5.6 7.5 6.5 5.3 7.1 5.1 5.7 6.5 5.9 5.9 5.6
Stddev. 2.1 2.2 2.1 2.0 2.6 2.1 2.8 2.6 2.0 3.1 3.1 2.0
QuestionCourse: EMLO (Likert scale of 1 to 5; n = 16)
3 4 7 10 11 13 15 16 17 18 19 20
Mean 4.3 4.0 4.1 3.8 4.3 4.3 4.3 3.7 4.5 2.8 3.9 2.7
Stddev. 0.9 0.8 0.5 0.6 0.6 0.6 0.5 1.1 0.6 1.2 0.8 0.9
Shapiro-Wilk .16 .13 .003 .14 .21 .04 .02 .04 .18 .004 .01 .06
Shapiro-Wilk <.0001 .02 .0004 0.09 <.0001
3838
Factors Affecting Scores (RN; Scores 1 - 10)
Item
Results
S
2- This class raises my interest for nutrition ……
1- My level of interest for nutrition is……………….
6.2
E W M U G
6.3
7- I need to build my expertise …… 7.3
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
.07
.10 7.1 8.3
12- The topics are relevant to me …… 6.7 .10 6.3 8.3
3939
Factors Affecting Scores (RN; Scores 1 - 10)
Item
Results
S
20- In-class discussions help me learn ……
19- The readings help me learn ………………. 6.2
E W M U G
6.9
22- Students should lead in-class discussions …… 4.1
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
<.01
.01 3.1 8.3
25- The Web-based quiz was useful …… 6.1
6.9 5.5 7.0 5.0 5.6 8.8
<.01 7.1 6.7 6.7 8.0
5.4 2.1
4040
Factors Affecting Scores (RN; Scores 1 - 10)
Item
Results
S
28- I am comfortable taking with instructor ……………..
26- Reading, quizzes and discussion fit together …. 6.8
E W M U G
6.7
29- Instead of discussion, I would prefer lecture …… 6.9
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
.01
43- I am learning a lot in this class …… 6.4
6.3 9.06.9 5.5
6.9 5.8 5.9 8.3
4141
Factors Affecting Scores (EMLO; Scores 1 - 5)
Item
Results
S
4- This course and its format stimulate my interest……….
3- The course topics are relevant …………………… 4.3
E W M U G
4.0
7- I am learning a lot in this class …………………. 4.1
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
10- Assignments encourage me to think …… 3.8 3.4 4.1
.01
3.6 4.4
3.9 4.4
4242
Factors Affecting Scores (EMLO; Scores 1 - 5)
Item
Results
S
13- E. material combined with class discussion works..
11- I am comfortable asking questions ………………… 4.3
E W M U G
4.0
15- E. Case studies were useful ……………………. 4.3
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
16- Electronic quizzes wereuseful …… 3.7
.01 4.0 4.6
4.3
4.1 4.5
4.0 4.6
.01
4343
Factors Affecting Scores (EMLO; Scores 1 - 5)
Item
Results
S
18- E. videos of the presentations were useful..
17- E. “summaries” of the presentations were useful.. 4.3
E W M U G
2.8
19- Web development should continue ………. 3.9
St*X
St=Student (P value); S=Survey; E=Evaluation; W=women, M=Men, U=underg., G=grad.
…………..Means …………
20- Additional time lecturing would be useful ………….. 2.7
.01
2.1 3.4
<.01
<.01 2.4 3.0
4444
Model Adequacy (paired vs. unpaired data)
Questions
Course: RN
1 2 7 12 19 20 22 25 26 28 29 43
Model U r2 .13 .30 .28 .39 .32 .25 .56 .22 .40 .57 .24 .62
Model P r2 .75 .60 .09 .09 .96 .94 .09 .68 .67 .48 .71 .73
Model U = Unpaired observationsn=36; rS = SE + Gder + Stg + SE*Gder + SE*Stg
Model P = Paired observations for 10 students,n=20: rS = ST + SE
4646
Summary and Conclusions
• Over the course of the semester, students’ perception of the benefits of reading assignments declined.
• Graduate students had a more positive attitude toward in-class discussion of readings than undergraduates
• Women were more inclined to find the readings helpful and were more “willing” to lead class discussion than men.
• Over the course of the semester, students’ interest for the course and its format increased
• E. case study and E. “summary” (transcription) of lecture material was ranked higher than E. quiz or videos
• Returning to lecture was not desired by students in this class
Ruminant Nutrition course
Environmental Management of Livestock Operations
4747
Summary and Conclusions
• Collecting “survey” data 3-4 wk in the semester and “evaluation” data at the end of the semester may be a useful tool for retrospective analysis of the “course dynamics”
• 1- 5 Likert scale yielded data that was not normally distributed
• 1-10 Modified scale yielded data that was normally distributed.
• Analysis of categorical data should most likely be performed on the ranked scores instead of the original scores
• It appears that paired observations would lead to more “powerful” statistical tests compared to unpaired observations.
The methodogy
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