Abstract
Statistics is interdisciplinary and the practical application of statistical methods in various areas prompts undergraduates to learn more about statistics and better understand complex methods. This article presents a classroom teaching design that guides students in reading COVID-19 literature. The activities presented encourage peer-peer and student-instructor interaction, which can be modified based on the type of course offered as well as the level and major of students by changing the articles required for reading. The teaching activities are designed with evidence-based teaching strategies such as scaffolding and connecting the activities to learning outcomes aligned with levels of Bloom’s Taxonomy. In our experience, the COVID-19 literature teaching activity improves students’ learning interest, cultivates students’ critical thinking, and enhances students’ understanding of theoretical methods. Supplementary materials for this article are available online.
1 Introduction
Knowledge is rapidly expanding in statistics, and many scientific articles dealing with new findings are published daily. Reading primary scientific literature can help fill the information gap between the material covered in textbooks and newly emerging data and evidence for revision of prior understanding (Ocaña-Riola Citation2016; Rawlings Citation2019; Anderson, Justement, and Bruns Citation2020).
The statistical literature includes mathematical theories and social applications. Undergraduates can better understand the social application literature because the social application literature often does not involve advanced mathematical principles (Lo and Hew Citation2021). Some researchers (Miller Citation2011; Freeman et al. Citation2014; Bonney Citation2015; Meyer et al. Citation2018; James, Cogan, and McCollum Citation2019; Anderson, Justement, and Bruns Citation2020; Cottone and Yoon Citation2020) have found that the use of real-world case studies is favorable to students. Case studies can improve critical thinking skills and help students apply the knowledge they have learned in class to practice. Therefore, this article presents a general process for using the primary literature on COVID-19 in statistical courses.
The outbreak of the COVID-19 pandemic has brought arduous challenges to social and economic development (Zoumpourlis et al. Citation2020). Statistics and related big data technologies have been pivotal during the pandemic. Statistics can be used for epidemic monitoring (Yoneoka et al. Citation2020; Cont, Kotlicki, and Xu Citation2021; Koum Besson et al. Citation2021), epidemic spread prediction (Ilie et al. Citation2020; Lee, Li, and Kim Citation2020; Mavragani and Gkillas Citation2020; Ozair et al. Citation2020), and precise prevention and control (Manevski et al. Citation2020; Corsi et al. Citation2021).
Although academic research on COVID-19-related topics has exploded (Fassin Citation2021), our study is the first to introduce the design of COVID-19 literature reading courses. In education, existing articles focused on the impact of COVID-19 on students’ learning status (Acevedo Citation2020; Essa, Subramanian, and Jayasuriya Citation2020; Lytras, Housawi, and Alsaywid Citation2021; Vatier et al. Citation2021). As far as we know, no article discusses how to use COVID-19-related literature to increase students’ statistical skills.
In this article, our main contribution is to design a classroom teaching activity to improve students’ statistical skills through COVID-19 literature reading. We use Jigsaw reading (Moskowitz et al. Citation1985; Ogawa Citation2018; Button et al. Citation2021) to organize the course activities and show that the design of activities follows Bloom’s Taxonomy six learning stages. Jigsaw reading is a cooperative learning technique. We choose Jigsaw reading as the activity class organization as Jigsaw reading seeks to make students active participants in the learning process (Alrassi and Mortensen Citation2020). The process of Jigsaw reading divides the students into groups, and each group reads only the corresponding section of the article. Then one student is selected from each group and merges to form a reconfigured group to study the whole article. Previous studies have found a positive effect of using Jigsaw reading on undergraduate education (Tarhan and Sesen Citation2012; Oakes et al. Citation2018; O’Leary, Barber, and Keane Citation2018; Baken, Adams, and Rentz Citation2020). Hence, our research contributes to both the literature on statistics course teaching design using COVID-19 examples and the literature on using Jigsaw reading in undergraduate education.
The article is structured as follows. Section 2 introduces the concept of Bloom’s taxonomy and illustrates our teaching activities divided by three lessons corresponding to Bloom’s taxonomy. Section 3 describes the data collection method. Section 4 presents the research questions issued by students after they are exposed to teaching activities and the results we find from the data. Section 5 provides some discussions. Section 6 concludes the article.
2 Teaching Activity Procedure
Bloom’s taxonomy is a valuable structure for lesson design (Zaidi et al. Citation2017; Verenna et al. Citation2018) as it can let instructors “see or hear” what the students have learned (Anderson and Krathwohl Citation2001). The categories of the cognitive processes are remembering, understanding, applying, analyzing, evaluating, and creating from lower-order to higher-order thinking skills. This section presents our teaching design in these six categories.
2.1 Teaching Objectives
In this section, we will discuss how we choose and use COVID-19 literature in various courses at our institution, and we will state our teaching goals in selecting each type of literature for each course.
Choosing articles suitable for undergraduate reading is very important. Sulaiman, Salehuddin, and Khairudin (Citation2020) stated that reading English academic texts could be a daunting task for many English as a Second Language university students. The complex features of literary texts, including academic discourse, text structure, and vocabulary, may affect the reading process. Although there are many statistical articles on COVID-19, undergraduates could not understand some articles that focus on methodological innovation very well. So we chose articles that focused on application innovation rather than theory innovation. Articles using some classical statistical methods may be more suitable for undergraduate study.
In different statistical courses, we choose the literature on various statistical methods. For example, presents the articles used in the Regression and Time Series Analysis courses. For Regression, articles on the COVID-19 issue are mainly on economic and social research, exploring the impact of COVID-19 on society (Barber et al. Citation2021). The Regression course is aimed at junior undergraduates majoring in statistics. This literature study can be carried out after the basic knowledge and theories of sampling design. For time series analysis, articles on the COVID-19 issue are mainly in the field of forecasting the trend of COVID-19 (Alzahrani, Aljamaan, and Al-Fakih Citation2020; Ilie et al. Citation2020). Another example in is the Time Series Analysis course. After completing the basic theory and practice of the stationary time series model, senior undergraduates can read the literature on statistical modeling of the number of people infected with the epidemic.
Table 1 Examples of articles chosen in regression and time series analysis.
Although the articles used in different classes vary, the primary teaching objectives are the same. First, students recall the statistical concepts in textbooks and identify and extract them from scientific research articles they read, corresponding to remembering in Bloom’s Taxonomy. Second, students understand how to apply statistical methods to test the articles’ hypotheses, corresponding to understanding in Bloom’s Taxonomy. Third, students communicate what they have learned with peers, corresponding to applying in Bloom’s Taxonomy. Fourth, students learn to analyze the results obtained from the figures and tables, corresponding to analyzing in Bloom’s Taxonomy. Fifth, students figure out whether the data and the experimental design can support the conclusions, corresponding to evaluating in Bloom’s Taxonomy. Lastly, students discuss what else can be found in the research, how to do better and develop ideas for future work, corresponding to creating in Bloom’s Taxonomy. presents the relationship between teaching objectives and Bloom’s Taxonomy. In Section 2.2, we will describe how to design and implement teaching activities to help instructors and students to achieve these objectives.
Table 2 The teaching objectives and Bloom’s Taxonomy.
2.2 Teaching Activities
In this section, we discuss a specific teaching activity in our class that uses COVID-19 literature. This teaching activity was carried out over three, 45 minute lessons where each lesson occurred in a separate, consecutive class period. Before the three lessons started, students were given the articles and asked to read them through and list the statistical terminologies extracted from the article, and this part was done outside of class time. The learning goal was to remember statistical concepts, methods, or principles and to understand how they work in the article. In this process, the students reviewed the fundamental theories and the steps of model establishment, and then they knew what and how to use these basic statistical concepts and methods in the articles. By reading literature, students connected the knowledge in scientific research papers with the basic theoretical knowledge in textbooks and further clarified the practical operation steps. Hence, this process belongs to remembering and understanding in the six learning stages of Bloom’s Taxonomy. In , we illustrate the activity procedure in the three lessons.
Table 3 The procedure in the three lessons.
In the first lesson, we applied Jigsaw reading (Ogawa Citation2018; Button et al. Citation2021) to discuss the main points in the article. We divided the class randomly into groups of size 4, with each group assigned one of the reading tasks given in . Then we reconfigured them into four reconfigured groups to study the whole article. takes What Explains Differences in Finance Research Productivity During the Pandemic? and Forecasting the Spread of the COVID-19 Pandemic in Saudi Arabia Using ARIMA Prediction Model Under Current Public Health Interventions as examples to illustrate the groups and tasks. In each group, every student reread the designated section of the article once again and discussed the difficulties when they read the paper before the beginning of the lesson. During the reading time, students read the details in the paper to point out the article’s main idea, why the author wrote this part, and what they learned. Students communicated, revised, and integrated their knowledge in each group within 15 min. After completing the prescribed portion of the study, each group member formed a reconfigured group. In our class, 40 students with serial numbers 1–10, 11–20, 21–30, and 31–40 formed the reconfigured group. In the reconfigured groups, every member read each part of the paper, and all members could be combined into a complete paper. In a reconfigured group activity, each student passed what they learned to the rest of the group. The whole group tried to answer a list of questions assigned by the teacher, which was provided in the last row of . This is the knowledge application stage of Bloom’s Taxonomy’s six learning stages.
Table 4 Groups, reading tasks, and assigned questions.
In the second lesson, which occurs after the Jigsaw reading activity, students made a PowerPoint presentation to show what they learned in the reconfigured groups and answered each question in . They had 25 min to make a PowerPoint and 20 min to do the presentation. Moreover, each group presented the mind map of the paper and answered the questions assigned before the lesson. The mind map described the problems and the statistical methods used in each part of the article. Each group representative showed the mind map and their group’s answers to the whole class. The instructor assisted the group with questions during the group work session. The learning goal was to analyze “what, how, and why” the statistical method was used in each part of the article. This stage is the knowledge analysis stage in the six learning stages of Bloom’s Taxonomy. Supplementary material gives one group’s mind map of the article What Explains Differences in Finance Research Productivity during the pandemic? in Regression class as an example to illustrate what the mind map is.
In the third lesson, after the PowerPoint presentation, the instructor and all students in the class commented on each group. The learning goal was to learn to make judgments about the statistical knowledge and understandings learned by peers. We voted based on rationality, logic, and fluency to determine the marks of each group. This process took about 15 min. This stage is the knowledge evaluation stage in the six learning stages of Bloom’s Taxonomy. More detail about awarding points is provided in the discussion section.
In the last 30 min of Lesson 3, each group proposed questions from the article for the class to discuss. The learning goal was to encourage the students to create some new knowledge based on what they have learned. Questions raised by students included some unknown concepts in the paper, problems with model improvement, and issues with specific practices. During the questioning process, students demonstrated their questioning and critical spirit. In solving the problems, each group of students searched for information on the computer, referred to the books, and had a discussion. Finally, they ended up with answers that most students agreed on, which showed the problem-solving ability of college students in the age of science and technology. We found that the students were interested in learning statistical methods as they put forward more questions on statistical models and tools than the other issues in the class discussion. This stage is the knowledge creation stage in the six learning stages of Bloom’s Taxonomy. Students improve their self-analysis and problem-solving skills in this process.
3 Data
This study was approved by the Institutional Review Board at the College of Economics and Management, Zhejiang Sci-Tech University, China. A survey was conducted on what problems students most want to know/investigate about the COVID-19 pandemic in the first 5 min at the beginning of the three lessons and the last 5 min at the end of the three lessons in the class of Regression. The students were all undergraduates in the economic and management school.
4 Results
At the beginning of the three lessons, a total of 47 questions were raised by 40 students (mean 1.175 questions per student). At the end of the three lessons, a total of 73 questions were raised by 40 students (mean 1.825 questions per student).
presents the frequency of the concrete issues of the questions put forward by students at the beginning and at the end of the three lessons. We can see that in every kind of problem, students put forward more concrete issues in the second survey than in the first survey. We concluded that students developed critical thinking abilities with subject-specific questions in the teaching activity. Moreover, students showed interest in statistical models and methods from the new issues in the second survey.
Fig. 1 Frequencies of issues at the beginning and the end of the three lessons.
shows that students put forward more questions at the end of the lessons than at the beginning of the lesson. Based on Paired t-test, we obtained t =–5.874, p < 0.0001, so the means of the number of questions put forward in the two surveys were significantly different. Based on the F test to compare two variances, we obtained F = 0.497, p-value = 0.032, so the variances of the number of questions put forward in the two surveys are different under the 0.05 significant level. We concluded that students developed their statistical learning interest and critical thinking ability by putting forward more questions at the end of the lessons.
Fig. 2 Frequencies of the number of questions put forward by students at the beginning and the end of the three lessons.
5 Discussion
The goal of scientific research article reading was to cultivate students’ statistical skills, including interest in statistics learning, communication ability in teamwork, and innovation ability in finding, analyzing, and solving problems. Before classroom learning, students did the literature reading, read the articles, and thought about the instructor’s list of questions. Students trained their reading ability, self-study ability, software practice ability, and literature searchability. In this classroom learning, students displayed how they communicate with peers. Students trained their organization, speech, and cooperation abilities.
To motivate every student to participate in the course, we made efforts in the reading literature selection, classroom organization, and course assessment.
First we took time to choose the reading articles. Reading too tricky or too easy literature could make students lose interest in learning and lose confidence in participating in course activities. Articles focusing on application innovation and involving basic statistical knowledge are better for undergraduate study.
Second, we used Jigsaw reading in our class to organize the active classroom. Jigsaw reading was a commonly used method in English teaching. Using Jigsaw reading for literature was one of our teaching methods’ innovations. The Jigsaw technique would help to develop learning, increase cooperation, enhance confidence, and help learners to be more active. Jigsaw reading provided the chance for students to work together. It helped students to improve or build relationships in classes. Before this activity, students often studied with the same partners because they did not have a chance to work with different partners. Therefore, the grouping in Jigsaw reading helped all learners in the same class to communicate, teach, and share knowledge (Alfares Citation2020). To help students not misunderstand that they would have the same scores as the other members of the same team, we adapted Jigsaw reading as Jigsaw reading ensures every student’s participation. Students completed the job in small groups and then went to the group to communicate their parts to others. Jigsaw reading prevented the students from relying too heavily on others. If they did not participate in the small group, they could not convey anything in the group to their peers. Generally, they did not want to be criticized by their peers, so they were active in group activities.
The third point to ensure student engagement rates was to develop fair assessments. In the group teaching technique, some students thought that they would be given the same assessment as their members in the same group, so they did nothing. Hence, the assessment for group learning was an essential part. The course assessment was a comprehensive process application, including self-assessment, peer assessment, and teacher assessment. There were two parts to the assessment system.
The first part was group evaluation. Students had their own estimated marks based on their performance in the activity learning, which was self-assessment. Each student would give the marks to the other members of the same team, which was peer assessment. The teacher would give a comprehensive mark. The teacher’s assessment based on each student’s performance was the teacher’s assessment.
The second part was the voting evaluation. The mark was given to the group according to the vote ranking, illustrated in Section 2.2 Teaching activities. This mark was the same for each member in the same group. Finally, the marks of the activity learning lessons were recorded as a part of the final marks, which was a process assessment. The results obtained under this assessment system reflected the students’ comprehensive quality.
gives the instructions and the percentage we took in the assessment process. In the supplementary material, we provided an example of an assessment table. Students could use the assessment table to give the marks, and then the instructors could collect the assessment table to calculate the mean as one student’s mark in the teaching activity learning. The assessment process follows Bloom’s Taxonomy’s six learning stages. Students estimate their marks and compare them to the marks given by their peers to determine if they have achieved the objectives in each of the six stages. The assessments based on the marks given by other team members focus on the process of study and are related to the first three stages of Bloom’s Taxonomy. On the other hand, the teacher’s assessment is based on the learning outcomes and focuses on the last three stages of Bloom’s Taxonomy.
Table 5 The instructions and the percentage we took in the assessment process.
Throughout the learning process, students showed a keen interest in statistical models. In the second lesson, many students asked the instructor why the article used the special statistical model instead of the others. In the third lesson, for further study, some students suggested that a deep learning technique might be a better tool for predicting the trend. In the survey, the trend or when we could stop it was the top concern for students. In conclusion, COVID-19-related scientific literature reading could improve students’ statistical skills, including stimulating students’ interest in statistical learning, cultivating students’ critical thinking, and enhancing students’ understanding of theoretical methods.
6 Conclusion
We designed a teaching activity conducting three lessons that follow the six learning stages of Bloom’s Taxonomy to guide undergraduates to read COVID-19 articles. Before the lessons started, students were surveyed about what they thought were the most concerning problems with COVID-19 and recalled the statistical concepts in textbooks. Then, students searched the statistical method used and tried to explain how the techniques were applied to test the hypothesis in the articles. Students participated in Jigsaw reading activities to read the literature and discuss it with peers. They analyzed the results obtained from the figures and tables and determined whether the data and experimental design could support the conclusions. Lastly, students created their thinking about the reading article. They put forward some questions about the reading article, trying to get the answers and pointing out what else could be developed for future work. From every group’s question list, we found that most questions were about the statistical methods used in the article. From the questions raised by students, we also found that the literature reading increased students’ interest in statistical methods. At the end of this teaching activity, students took a survey for the second time. They wrote down what they were concerned most about COVID-19. From the result, we could see that most problems written by students were hot topics in the academic field. Comparing the two surveys, we found that students had more concerning problems in the second survey at the end of the teaching activity. Thus, in our experience, the COVID-19 literature teaching activity stimulated students’ interest in statistical learning, cultivated students’ critical thinking, and enhanced students’ understanding of theoretical methods. The limit of the study was that the same students took the pre- and post-lesson surveys. Although more new problems were raised the second time, it would be natural that students could put forward more questions the second time than the first. Maybe different students with the same numbers taking the pre-lesson survey and post-lesson survey would be better.
supplements.zip
Download Zip (162.5 KB)Supplementary Materials
In the supplement, we provide the data and code used to produce the analyses in this article. The assessment table can help instructors to give marks to each student in the teaching activity.
Data Availability Statement
The data and the code in this article are available at https://github.com/zjwzajyl/teaching.
Disclosure Statement
The authors declare no potential conflict of interest.
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