Task 3: Assessing students’ information competencies

The requirement of the current task is to assess STA 151 coursework assignment and to determine to what extent it offers opportunities for authentic development of students’ information competencies.

A. Description of the task: What are students required to do?

In STA 151 various assignments are formulated as exercises; therefore, the current task is a selected exercise.

A family desires to have 5 children. The probability that a child being born boy and girl is 0.5 and if it is assumed that the presence of twins’ is excluded:

1.1  Find the suitable distribution between binomial and Poisson. Justify your answer.

1.2  Draw the tree diagram to determine all outcomes and probabilities.

1.3  Suppose X is a random variable that indicates the number of boys, determine the probability distribution of X by using binomial distribution.

B. What are the primary learning outcomes that are assessed through this assignment?

 The primary learning outcomes that are assessed through this assignment are:

To check the level of understanding and comprehension of students towards the application of binomial and Poisson distributions;

To draw the tree diagram and to determine all possible outcomes and probabilities;

To determine and describe the random variable X;

To apply the binomial distribution and to determine the probability distribution of X.

C. Consider whether students are given clear guidance in respect of information sources to be used

In respect of information sources to be used by students, it should be noted that the module has the Course Reader and this course reader serves as guidance for students. In addition, besides the course reader, others sources were recommended to students like statistics books and internet.

D. Is there any recognition of the underpinning information tasks and skills that may be necessary to fulfill the assignment? Is provision made for supporting students in these?

Through the Course Reader and any other statistics books, students should be able to find the rules that underpin the binomial distribution. These rules include the independence of trials, the number of trials is n and it is fixed, each trial outcome is classified as success or a failure, k as a number of desired success is supposed to be greater or equal than the number of trials and p is the probability of success for each trial and p remains the same for each trial. Hence, students are initiated to the experiment that requires the application of binomial distribution and find the probabilities. The Course Reader also provides the rules of Poisson distribution.  Further, the Course Reader indicates the similarities between Poisson and binomial such as independence of trials, each trial outcome is classified as success or a failure and difference such as the number of trials which is n, is fixed for binomial but it is not for Poisson, where the trials come in recurrent intervals.  

E. Is this specified as part of the criteria for performing the task, and awarded credit?

Definitely yes, any task given to the students is to check their level of understanding, application and to award them with marks. This assignment was marked on 20 marks and the marks were added to cum marks for the all module.  

F. How could this assignment be re-designed to explicitly build and recognize students’ information literacy competencies?

Given we had chance to mark the assignment; it was identify the mistakes that students have made and the prerequisite necessary in order to achieve the assignment. The assignment should be re-designed into two different questions.

Question 1

1.1 List the conditions to apply the binomial distribution.

1.2 What is the difference between binomial and Poisson Distributions?

Question 2

A family desire to have 5 children. The probability that a child being born boy and girl is 0.5 and if it is considered that they are no twins’ case taking in account:

2.1  Between binomial and Poisson distribution which is the most appropriate and justify your answer.

2.2  Draw the tree diagram to determine the all outcomes and probabilities.

2.3  Suppose X is a random variable that indicates the number of boys, determine the probability distribution of X by using binomial distribution.

Task 2: Critique of STA 151 module outline

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.4^th Edition. New York.

Moore,D., McCabe, G.P. & Craig, B. A.(2009). Introduction to the Practice of Statistics.6^th Edition. New York.

Henry,M.(2009). Guide to writing Module Learning Outcomes at DCU.

http://teachingcommons.depaul.edu/Course_Design/developing_a_course/design.html.