WGU D389 TASK 2
LEARNING STRATEGIES IN HIGHER EDUCATION | 2026/2027
UPDATE
WESTERN GOVERNORS UNIVERSITY Complete Task with Complete
Solution | A+ Graded
SECTION 1: COURSE-SPECIFIC STRATEGY APPLICATION
Target Course Identification For the purpose of this task, the target course selected is C955:
Applied Probability and Statistics. This course was chosen due to its quantitative nature and the
necessity for both conceptual understanding and procedural application, which presents distinct
challenges compared to humanities or theory-based courses.
Course Content Analysis C955 focuses on the practical application of statistical methods. The
core concepts include:
1. Descriptive Statistics: Measures of center (mean, median, mode) and spread (variance,
standard deviation).
2. Probability Distributions: Understanding the normal distribution, z-scores, and the
Central Limit Theorem.
3. Inferential Statistics: Hypothesis testing, confidence intervals, and determining statistical
significance (p-values).
4. Correlation and Regression: Analyzing relationships between variables.
The primary assessments consist of objective assessments (multiple-choice exams) requiring the
calculation and interpretation of data sets.
Subject-Specific Learning Strategies Given the STEM nature of this course, specific strategies
distinct from humanities courses are required:
• Problem-Solving Interleaving: Instead of practicing one type of problem repeatedly
(blocked practice), I will utilize interleaving. This involves mixing different types of
problems (e.g., probability, z-scores, and regression) during a single study session.
Research by Rohrer (2012) indicates that interleaving improves discrimination between
problem types, which is critical in statistics where determining the correct test to use is
often harder than performing the calculation itself.
, • Scaffolded Practice: I will begin with "worked examples" where I follow a step-by-step
guide to solve a problem. As competency increases, I will remove the scaffolding—first
attempting the problem without notes, then checking the solution, and finally solving
novel problems independently.
• Conceptual vs. Procedural Knowledge: In Statistics, it is vital to separate the
memorization of formulas (procedural) from the logic behind them (conceptual). I will
utilize the "Teach-Back" method, attempting to explain why a specific formula is used for
a specific data set to an imaginary audience. This leverages the Feynman Technique to
identify gaps in understanding.
Strategy Adaptation to Course Format As WGU is a fully online, competency-based institution,
the course format lacks synchronous lectures. To adapt:
• Asynchronous Engagement: I will supplement the provided textbook with external visual
aids, such as Khan Academy videos, to visualize concepts like the normal curve.
• Digital Note-Taking: Using a tablet or stylus, I will hand-write formulas and equations.
Mueller and Oppenheimer (2014) found that handwriting notes leads to better
conceptual understanding than typing, which is particularly relevant for mathematical
notation that is difficult to type efficiently.
SECTION 2: ASSESSMENT PREPARATION
Exam Preparation Strategy
• Study Guide Creation: I will create a "One-Page Summary" for each module. This
summary will not list every formula but will create a "Decision Tree" flowchart. For
example: "Is the data categorical or quantitative? If categorical -> Chi-Square. If
quantitative -> t-test." This aids in the high-level cognitive task of selecting the correct
statistical tool.
• Retrieval Practice Schedule: Instead of re-reading the textbook (a passive strategy with
low utility), I will employ retrieval practice (Karpicke & Blunt, 2011).
o Day 1: Study a concept (e.g., Hypothesis Testing).
o Day 2: Attempt to write down everything I know about Hypothesis Testing
without looking. Check accuracy.
o Day 4: Solve 5 practice problems on Hypothesis Testing.
LEARNING STRATEGIES IN HIGHER EDUCATION | 2026/2027
UPDATE
WESTERN GOVERNORS UNIVERSITY Complete Task with Complete
Solution | A+ Graded
SECTION 1: COURSE-SPECIFIC STRATEGY APPLICATION
Target Course Identification For the purpose of this task, the target course selected is C955:
Applied Probability and Statistics. This course was chosen due to its quantitative nature and the
necessity for both conceptual understanding and procedural application, which presents distinct
challenges compared to humanities or theory-based courses.
Course Content Analysis C955 focuses on the practical application of statistical methods. The
core concepts include:
1. Descriptive Statistics: Measures of center (mean, median, mode) and spread (variance,
standard deviation).
2. Probability Distributions: Understanding the normal distribution, z-scores, and the
Central Limit Theorem.
3. Inferential Statistics: Hypothesis testing, confidence intervals, and determining statistical
significance (p-values).
4. Correlation and Regression: Analyzing relationships between variables.
The primary assessments consist of objective assessments (multiple-choice exams) requiring the
calculation and interpretation of data sets.
Subject-Specific Learning Strategies Given the STEM nature of this course, specific strategies
distinct from humanities courses are required:
• Problem-Solving Interleaving: Instead of practicing one type of problem repeatedly
(blocked practice), I will utilize interleaving. This involves mixing different types of
problems (e.g., probability, z-scores, and regression) during a single study session.
Research by Rohrer (2012) indicates that interleaving improves discrimination between
problem types, which is critical in statistics where determining the correct test to use is
often harder than performing the calculation itself.
, • Scaffolded Practice: I will begin with "worked examples" where I follow a step-by-step
guide to solve a problem. As competency increases, I will remove the scaffolding—first
attempting the problem without notes, then checking the solution, and finally solving
novel problems independently.
• Conceptual vs. Procedural Knowledge: In Statistics, it is vital to separate the
memorization of formulas (procedural) from the logic behind them (conceptual). I will
utilize the "Teach-Back" method, attempting to explain why a specific formula is used for
a specific data set to an imaginary audience. This leverages the Feynman Technique to
identify gaps in understanding.
Strategy Adaptation to Course Format As WGU is a fully online, competency-based institution,
the course format lacks synchronous lectures. To adapt:
• Asynchronous Engagement: I will supplement the provided textbook with external visual
aids, such as Khan Academy videos, to visualize concepts like the normal curve.
• Digital Note-Taking: Using a tablet or stylus, I will hand-write formulas and equations.
Mueller and Oppenheimer (2014) found that handwriting notes leads to better
conceptual understanding than typing, which is particularly relevant for mathematical
notation that is difficult to type efficiently.
SECTION 2: ASSESSMENT PREPARATION
Exam Preparation Strategy
• Study Guide Creation: I will create a "One-Page Summary" for each module. This
summary will not list every formula but will create a "Decision Tree" flowchart. For
example: "Is the data categorical or quantitative? If categorical -> Chi-Square. If
quantitative -> t-test." This aids in the high-level cognitive task of selecting the correct
statistical tool.
• Retrieval Practice Schedule: Instead of re-reading the textbook (a passive strategy with
low utility), I will employ retrieval practice (Karpicke & Blunt, 2011).
o Day 1: Study a concept (e.g., Hypothesis Testing).
o Day 2: Attempt to write down everything I know about Hypothesis Testing
without looking. Check accuracy.
o Day 4: Solve 5 practice problems on Hypothesis Testing.
