The Raising Factor, That Great Unknown. A Guided Activity for Undergraduate Students

Figures & data

Table 1 Activity design.

SRLE principles	Learning goals	Activity steps
Focuses on developing central statistical ideas rather than on presenting set of tools and procedures.	Preliminary step	Step1
Uses real datasets to engage students in making conjectures.	LG 1: Students become familiar with an official data base and realize that even if data are available, skills to manage that data are required to extract and understand the information.	Step 2
Uses real datasets to engage students in making conjectures.	LG 1: Students become familiar with an official data base and realize that even if data are available, skills to manage that data are required to extract and understand the information.	Step 3
Integrates the use of appropriate technological tools that allow students to test their conjectures and develop their statistical reasoning.	LG 2: Students learn to extract the required information from an official database and compose their own data frame with the required variables. They also are exposed to the use of R software.	Step 4
Uses activities to support the development of students’ reasoning.	LG 3: Students match theoretical concepts with their own data analysis to obtain their own conclusions.	Step 5
Focuses on developing central statistically ideas rather than on presenting set of tools and procedures.	LG 4: Solving real cases implies a deep understanding of matter and being able to relate concepts to obtain conclusions.	Step 6
Uses activities to support the development of students’ reasoning.	LG 5: Students reflect on their learning in the activity and are provided with some useful autonomous work.	Step 7

Fig. 1 A data section. This figure just shows a piece of data as an example of the data base structure. We did not include the whole data base for a more reader-friendly approach.

Fig. 2 R script to create data frame.

Fig. 3 R Script. Mean calculation.

Table 2 Students’ favorite teaching approaches.

Teaching approaches	Mean (SD)
Practical lesson, solving exercises on the blackboard	6.2 (1.2)
Practical lessons, solving real cases with real data	5.5 (1.6)
Theoretical lessons	4.5 (1.6)
Working in groups	4.3 (2.0)
Practical lessons solving exercises with the computer	4.0 (1.8)
Individual work, studying from textbooks	3.9 (1.8)

Table 3 Use of R and economics in the media.

Question	Yes answers
Before this statistic course, had you ever used the R software?	6%
Were you able to follow the activity correctly?	67%
Do you usually read media news items related to statistical and/or economic content?	27%

Table 4 Skills developed during the activity.

Skills	Mean (SD)
1. Find links between the subject of statistics and economic reality.	5 (1.4)
2. Familiarize myself with the management of large databases and access information sources.	5 (1.4)
3. Better understand the economic situation and its implications.	4.9 (1.4)
4. Improve my ability to summarize a problem and know how to interpret the results I have obtained.	4.8 (1.4)
5. Improve my ability to better assess and plan for the resolution of a complex problem	4.7 (1.4)
6. To better understand the theoretical concepts of statistics and to know how to apply them when solving economic problems.	4.7 (1.5)
7. Improve my technical vocabulary in the specific fields of economics and statistics.	4.6 (1.6)
8. Improve my skills in using R software.	4.6 (1.7)
9. Improve my critical thinking for solving problems.	4.5 (1.4)
10. To better understand the economic news content.	4.5 (1.4)

Fig. 4 Students’ opinion about the activity.