Task 2: Critique of STA 151 module
outline
(Do you think this STA 151 module outline is useful for your students?
If your answer is yes, in what ways is it useful? If your answer is no, can you
recommend ways of improving its design?).
The course design is a cyclical process which has numerous models.
This presentation will criticize the module outline for STA 151 by considering
the following steps (1) analyze the students, (2) design goals comprising
learning outcomes, objectives, assessments and activities, (3) develop learning
materials and activities, (4) Implement instructions to run the course and (5) set
up the right guide for evaluating students achievement and course evaluation (Whetten,
A.D.: 2007).
Student
analysis
The analysis of students required the lecturer to identify student’s
background and define what they need to know in the module. In general, the
current design of the module conceived for ECP students is very good, because
it respects the goals of statistics as argued by Moore (2007: xxiii). He states
that the goal of statistics is to gain understanding from data. Since the data
are expressed as a set of numbers and the numbers are meaningful with a
context. Hence, the context makes the number informative for the users. The
numbers engage the background knowledge and allow the users to make judgement
(Moore,D. 2007:xxiii; Moore et al., 2009).
In view of that, the module of STA 151 was developed in the context of requirements
to consolidate the basic practice of statistics of students for life. It is
designed in chapters and each chapter in sub-sections. In this vein, it tries
to empower the students with the techniques of data collection, data analysis
and interpretation of data. In this regard, I agree with the course
design principles and the course design process as it is published so far. In spite of that, its content fits
with the expectations on basic practice of statistics for life, some recommendations
will be mentioned during this discussion.
Design
goals comprise learning outcomes and objectives, assessments and activities
Henry (2011) defines the module learning outcomes as specific
activities that students will be able to do and they assist students to achieve
the objectives. The current STA 151 design determines the content, delivery and
assessment of each activity and along with other modules meet the programme
outcomes. The module learning outcomes of STA 151 inform students of what is
expected of them, it serves as a guide for the lecturer, TA and tutors in the
approach of delivering the content and assessment that focus on what the
students will be able to do as a result of learning. It influences the domain
and levels of learning required for the delivery and assessment and finally
fulfil the requirements of one or more programme outcomes. STA151 includes twelve
chapters as follow: Little mathematics first, introduction to statistics,
measures of central and dispersion, the standard deviation and normal
distribution, sampling methods, probability, random variable and probability
distributions, confidence intervals, hypothesis testing, chi-square tests,
analyses of variance and correlation.
However, given that the current discussion will be reviewing
chapter by chapter, few suggestions will be pointed out for the improvement of
the current design of the module. It starts with little mathematics first as
chapter one. In doing so, the module has opted the best option for activities
learning because the little mathematics first prepares students and gives them
a complete background of mathematics that are needed in statistics. However, it
might be added to the notion of sets and combinatorics in short. The chapter
two is titled ‘Introduction to statistics’ and ensure students understand the
basic concepts of statistics; construct a frequency distribution and construct
different graphical presentations of data in order to improve their capacity
for data collection, data analysis and interpretation. Chapter three explored
the measures of central and dispersion. Through the measures of central and
dispersion, students are prepared not only to compute the measures of central
and dispersion but are also prepared to know how to apply the measures of
central and dispersion. With the standard deviation and normal distribution
chapter, students might be able to rescale and shift data by factors, to use
the Z-score for comparison and to test the normal assumption before using the
normal distribution. By learning the sampling methods chapter, students are
informed why the sample is important to learn about population. In this respect,
they are advised of the issue of representativeness of the sample and sampling
techniques. The following chapter is probability, the design of this chapter to
me; needs to be revised, in a sense that the chapter might not be started with
probability concepts but introduction first of all the concepts of sets and
counting such as factorial, combination and permutation, Venn and tree diagrams.
In starting by the concepts of sets and combinatorics students will be
familiarised with concepts of probability in easy way. It could be also added
the Bayes’ theorem. With chapter seven named ‘random variables and probability
distributions’, besides the actual content, I suggest that it could be added
the hyper geometric and multinomial distributions. In chapter eight ‘confidence
interval’ and nine ‘hypothesis testing’, there is a need to insert a section
which indicates the clarifications of the link between confidence interval and
hypothesis testing. Furthermore, it is advisable to add the concept of p-value
and its computation in context of Z-test in order to provide for students
different ways to handle the decision on the hypothesis testing and the section
dealing with sample size. The design of the activities learning in the remaining
chapters 10, 11 and 12 are well applied and I do not have particular comments
on it.
Develop
learning materials and activities.
So far, there is no problem in the design of STA151 learning with
regard to learning materials and activities because materials and activities are
developed such as in textbooks, readings, simulations, interactive digital
materials, and online resources are needed for the activities, computer,
calculator and assessments.
Implement
instructions to run the course and Guide for evaluating students’ achievement and course evaluation
The STA 151 module has to date in its design a clear instruction
and adequate guide for evaluating students’ achievement and course evaluation. The
evaluation and assessment tasks are fixed on various dates that are communicated
to students before the beginning of each term. Students are informed in beginning of the module that they will be evaluated with 12 tutorial tests, 3 tests, one final exam at the end of the year. A student has given second sit as supplementary exam if failed the first exam according to the regulations of the university. With regard to cum marks, students are informed that only 10 best tutorial tests and 2 best test will be selected for the cum marks. The pass mark that allow student to write a final exam is 40% in cum marks.
References
Whetten,A.D. (2007). Principles of effective course design:
what I wish I had known about learning-centred teaching 30 years ago. Journal of Management Education. 31(3):
339-357.
Moore,D. (2007). The Basic Practice of Statistics.4th Edition. New York.
Moore,D., McCabe, G.P. & Craig, B.
A.(2009). Introduction to the Practice of
Statistics.6th Edition. New York.
Henry,M.(2009). Guide to writing
Module Learning Outcomes at DCU.
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