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Research Article | | Peer-Reviewed

Enhancing SPSS Proficiency and Operational Competencies Among 4th Year Statistics Students at Wolkite University: An Action Research Study

Debebe Landina Lata*,  Bontu Habtamu,  Netsanet Mamo,  Rahel Kedir,  Misgana Tekle,  Yitages Negede
Published in Advances (Volume 6, Issue 2)
Received: 7 May 2025     Accepted: 26 May 2025     Published: 23 June 2025
Views:       Downloads:
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Abstract

Statistics is essential in daily life, making it crucial for educators and learners to master its use and interpretation. Statistical Package for the Social Sciences (SPSS) statistical software helps avoid mathematical errors and ensures accurate results for researchers, students, and educators. Statistical analysis is crucial for drawing meaningful conclusions in modern research across various disciplines. It also helps students present their research effectively and empowers professionals to interact with data, promoting creativity and innovation in their fields. The main objective of the research was to improve the skills of Wolkite University's fourth-year statistics students by enhancing their operational skills in statistical SPSS software. The data from the student questionnaire was tabulated and analysed using descriptive statistical methods, and the student's performance before and after the training was recorded using inferential statistics. The SPSS version 27 software was used to analysed the collected data. From the descriptive statistics of the total 23 (100%) students, the proportion of male and female students is 20 (86.96%) and 3 (13.04%), respectively. Before the training, of the total of 23 (100%) students, 19 (82.6%) had good skills, and the remaining 4 (17.4%) students had very good skills. However, 13 (56.5%) students had excellent skills after training, and the remaining 10 (43.5%) had excellent skills in SPSS software. The proposed actions for increasing the performance of students in SPSS were focused on improving basic statistical data using SPSS statistical software.

Published in Advances (Volume 6, Issue 2)
DOI 10.11648/j.advances.20250602.16
Page(s) 73-80
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2025. Published by Science Publishing Group
Previous article
Keywords

Operational, Statistics, SPSS, Statistical Software

1. Introduction
Education plays a key role in the development of a country. Our country, Ethiopia, is prioritizing education for development by expanding universities, colleges, and technical vocational schools, increasing university intake capacities, fostering university-industry linkages, and enhancing science and technology programs. Ethiopian universities are adopting active learning techniques
[1, 2]
. Educational assessment, like improving SPSS software, requires a clear conception of all intended learning outcomes of the instruction and a variety of assessment procedures
[3]
. Educational entities have the freedom to choose their developmental trajectories and objectives. Utilizing statistical software like SPSS is vital in contemporary statistical analysis in various sectors, including academia, industry, and research
[4]
, to evaluate student attitudes and achievements
[5]
.
IBM's SPSS is a robust software extensively used to address technical challenges in data-centric tasks
[3]
. (Aragaw Asfaw et al., 2022). Statistical analysis is crucial for drawing meaningful conclusions in modern research across various disciplines
[6]
. IBM SPSS has emerged as a widely utilized tool for data analysis, offering extensive analytical capabilities and user-friendly features
[4]
. Despite its widespread use, there is a gap in research that systematically examines SPSS's impact and importance
[7, 8]
. First released in 1968 as the SPSS
[9]
, it continues to be a favored tool for quantitative data analysis. Since IBM's acquisition in 2009, it has been officially named IBM SPSS Statistics, but it is still widely known as "SPSS" among users
[10]
. The software greatly simplifies the analysis of extensive datasets, conserving time and effort. SPSS's statistical analysis capabilities support various research phases, including data gathering, presentation, interpretation, analysis, and conclusion
[11]
. It serves as a tool for researchers, students, and educators to eliminate manual calculation errors and achieve accurate results, provided the data input is precise
[12]
. SPSS is popular among students, researchers, professionals, and scientists for predicting future trends accurately and clearly through statistical analysis
[13]
. It also helps students present their research effectively and empowers professionals to interact with data, promoting creativity and innovation in their fields
[11, 14]
. The importance of SPSS in research cannot be overstated, as it caters to the diverse needs of researchers across various fields such as social sciences, health services, business, and education. Its user-friendly interface, extensive analytical capabilities, and robust statistical techniques have contributed to its rapid adoption in recent years
[15]
. Researchers rely on SPSS to efficiently organize, process, and analyze data
[16]
. Despite its widespread empirical use, there exists a gap in systematic research examining SPSS's impact and significance in research practices. While anecdotal evidence suggests its usefulness in enhancing research outcomes, a comprehensive understanding of its role and effectiveness remains elusive.
Enhancing student engagement in SPSS statistical software skills is vital for bolstering the teaching and learning process, as it improves understanding and retention of statistical analysis techniques
[17, 18]
. (Chen & Liang, 2025; Cujba & Pifarré, (2024). We have observed that students' engagement in enhancing their SPSS skills is minimal due to a lack of familiarity with statistical analysis. Low students’ practical skills in knowing and implementing SPSS statistical software are the factor that hinders students’ academic achievement and performance in science education. In the statistics laboratory room, students’ active involvement is necessary to increase their operating skill levels when applying SPSS statistical software. I am teaching this student statistical computing-I course, and I deliver a practical mid-exam (30%) for them, and the exam covers opening, data entry, coding, importing and exporting data, analysis, and reading the output. From this, most students were unable to do import and export, analysis, and reading the output. Generally, students scored below half, which means that out of 30, only nine students scored above 15. As an instructor, the existence of such a problem prompts me to develop action research on the topic of improving the operating skills of SPSS software for fourth-year statistics students.
Typically, students at this stage are introduced to statistical software, activities, and fundamental principles. Classrooms should be equipped with the necessary resources and guidance to facilitate meaningful exercises and experiments that bolster students' comprehension of statistical analysis. This challenge has led us to explore methods to boost students' academic performance and interest in statistical methods. This study is significant in developing strategies for the professional growth of academic staff, in line with their readiness to employ statistical software packages with undergraduate students. Therefore, the goal of this action research is to improve the SPSS statistical software skills of 4th-year undergraduate statistics students at Wolkite University, Ethiopia, in 2024.
2. Research Methodology
2.1. Study Area
The experiment was conducted at Wolkite University, College of Natural and Computational Science, for statistics 4th-year students in 2024. Wolkite University is one of the higher education institutions in Ethiopia. Wolkite (also transliterated Wolkite) is the capital town and separate woreda in southwestern Ethiopia. The administrative centre of the Gurage zone, this town has a latitude and longitude of 8°17′N, and 37°47′E, and is about 158 km and 256.4 km far from Addis Ababa and Hawassa, respectively. The Gurage Zone comprises altitudes ranging from 1001 to 3500 meters above sea level. Based on the local agro-climatic classification, the zone is classified into three agro-climatic zones. Dega (excessive altitude) covers 28.3% of the area and ranges between 2500-3662 mass; Weinadega (mid-altitude) at 1500–2500 mass encompasses about 64.9% of the area; and Kola (lowland) at 100–1500 mass covers 6.8% of the area. The average annual minimum and maximum temperatures and rainfall ranged from 18°C to 39°C and 450 to 820 mm, respectively.
2.2. Target Group
The target groups of this action research were 4th-year statistics students, which were 23 in number; out of these, 20 were males and 3 were females, respectively. Fourth-year students were selected because they lack data analysis skills and use statistical software efficiently. To be efficient with statistical software, it takes training and practice using SPSS. Therefore, this action research was implemented in the mentioned department to fill this gap.
2.3. Methods of Data Collection
In our study aimed at enhancing students’ SPSS statistics software skills at Wolkite University, we gathered data from primary sources such as questionnaires, focus group discussions, and observations involving fourth-year statistics department students. Additionally, we reviewed various books and research conducted by different scholars to inform our study. A total of 23 students participated in the questionnaire distribution.
2.4. Method of Data Analysis
In this study, the data was organized in a table and expressed descriptively using statements, and comparisons were made between before and after the intervention of strategies, and then the results were expressed either in statements or percentages. First, the data was organized and managed based on the action research objectives and will be entered and analyzed using SPSS version 27. The quantitative data includes frequency, percentage, and a paired sample t-test. Results were presented using tables.
2.5. Statistical Software
For the analysis of the provided data, SPSS latest version 27 software was used, and a significant level of alpha 0.05 was employed for conducting statistical tests.
2.6. Planned Action
Students’s improvement in statistical software is very important because it helps them learn more. As researchers, we tried to solve the above-stated problem using different activities. After identifying the problem, we developed an action plan that is listed below. The implementation of an action plan was mandatory to solve current problems. From the beginning, the major concern of the study was improving Wolkite University fourth-year statistics students’ operational skills in using SPSS software in handling, organizing, presenting, and analyzing statistical data. As researchers, we collected information from a questionnaire survey, an interview, and our observations. After all, based on the above information from the 4th year statistics department, we already confirmed the presence of the problem, and we designed the action plans into the following categories or parties in the table below for training (Table 1).
Table 1. Description of the action plan categories flow.

Categories

Descriptions of the Activities

Activities in each category

Problems will be solved

Time frame

C-1

Training on introducing how to start SPSS for Windows.

Opening and exiting SPSS, creating a data file, data entry, importing and exporting data from Excel.

Opening SPSS, data entry, saving data

Morning and afternoon

C-2

Mastering data management techniques using SPSS.

Inserting new variables, labelling variables and values, deleting variables, cleaning data with SPSS, splitting files, merging data and files, transforming variables, and creating indicator variables.

Manage data using software (coding data, editing of data, imputing missing data, and treatment of outliers).

Morning and afternoon

C-3

Developing proficiency in conducting descriptive statistical analysis using SPSS.

Measures of central tendency (mean, median, sum, quartiles…), measures of variations, using different types of graphs (histogram, bar chart…), the relationship between categorical variables (cross-tabulation, chi-squared test),

Exploring descriptive Statistics measure of variation, frequency, percentage

Morning and afternoon

C-4

Improving their skills in inferential Statistical techniques

Association between numerical variables (correlation), t-test, analysis of variances, Linear regression, Binary Logistic regression model, and output reading.

Performing Inferential Statistics using SPSS (test of association, linear regression, logistic regression, and output reading

Morning
2.7. Implementation of Planned Action
To improve the student’s statistical software operational skill level in basic data handling, organization, presentation, and analyzing statistical data using SPSS statistical software in the statistical computing-I course for Wolkite University fourth-year statistics students, the following actions were taken into consideration: The possible solution of this action research was to facilitate and intensively assist in various interventions for improving students’ software skills, like data handling, data organization, presentation, and analysis of statistical data.
Therefore, we developed and planned the following tasks to minimize the problems that lead to low student improvement levels in the computer lab activity.
1. One period was used for training about the importance of SPSS for students, rules and regulations in computer laboratories, and the handling skills of lab equipment’s computers.
2. Interactive oral teaching was delivered to students before the start of training.
3. An active teaching method suitable for computer lab activity and bringing high student improvement levels was used.
4. Guidelines to practice SPSS before the start of training were provided.
5. Teaching aids like videos that support SPSS training were utilized.
6. A group was formed that had a mixture of low-, medium-, and high-achievement students.
7. Specific tasks were provided for each individual and group member, like data entry, data cleaning, data transformation, analysis, and output reading.
8. Marks were assigned for each computer lab session (training) as reinforcement.
3. Results and Discussion
The main objective of this study was to improve students' SPSS software skill performance in the Wolkite University fourth-year statistics department. The data were collected from the 4th year statistics undergraduate students, and we used all statistics fourth-year students (a total of 23 students) for our data collection because they were small in number. In this section, the results obtained through the questionnaire, interview, and training (before and after) from the data source (students) are presented and analyzed. Of them, 20 were male and only 3 were female (Table 2).
Table 2. Summary statistics for assessing the variation of SPSS software for Statistics 4th-year students.

ID No.

Sex

Residence

Age

Awareness before training

Awareness after training

1

1

1

1

1

3

2

1

1

2

1

2

3

1

0

1

2

2

4

0

0

2

1

3

5

1

0

2

1

2

6

0

0

2

1

2

7

1

1

1

1

3

8

1

0

2

1

2

9

1

1

2

1

2

10

0

1

2

2

3

11

1

0

2

1

3

12

1

0

3

1

2

13

1

0

2

2

2

14

1

0

1

2

2

15

1

1

2

1

3

16

1

1

2

1

3

17

1

0

1

1

3

18

1

1

2

1

2

19

1

0

2

1

3

20

1

1

3

1

2

21

1

0

2

1

2

22

1

0

3

1

3

23

1

0

2

1

2
Key terms: Sex: female=0, male=1; residence: Urban=1, Rural=0; Age: 17-21=1, 22-26 =2, above 26 =3; Awareness before training: good=1, v. good=2, excellent=3; Awareness after training: good=1, v. good=2, excellent=3
3.1. Descriptive Statistics
There were 23 students in total, with the gender distribution being 20 males (86.96%) and 3 females (13.04%), as shown in Figure 1. This indicates that the majority of the 4th-year statistics students were male.
Figure 1. Number of students on gender.
According to Figure 2, all 23 students (100%) were assessed for their skills in SPSS software before training. Among them, 19 students (82.61%) were found to have good skills, while 4 students (17.39%) had very good skills. These results suggest the necessity for software training to enhance the student's proficiency in SPSS.
Figure 3 presents post-training data for the same 23 students, showing that 13 students (56.5%) had very good skills in SPSS, and the remaining 10 students (43.5%) had excellent skills. This demonstrates the effectiveness of the training in significantly improving their software skills.
Figure 4 indicates the geographic background of the 23 students: 14 students (60.9%) were from rural areas, while 9 students (39.1%) were from urban areas.
Figure 2. SPSS software operating skill before training.
Figure 3. SPSS software operating skill after training.
Figure 4. Students place of residence.
Figure 5 shows the age distribution of the 23 students: 5 students (21.74%) were aged between 16-20 years, 15 students (65.22%) were aged between 21-25 years, and 3 students (13.0%) were aged 26 years or older.
3.2. Test of Association Between Pre- and Post-Training
The researchers prepared pre- and post-test questions for students, and the results were recorded and analyzed before and after SPSS training. After training, their skill in data analysis improved. Table 3 shows that 23 students participated in the training, the average mid-exam score of the pre-training students was 1.1304, and the post-training mean mid-exam score was 1.913. It seems that the students scored better after obtaining training, the standard deviation score of pre-training was 0.344 (34.4%) and the standard deviation post-training score was 0.596 (59.6%). This result showed that in the pre-training session, there was small variability (34.4%), which means that almost all students had the same skill level, and in the post-training session there was relatively high variability (59.6%), which means there were dispersed exam scores among students. Table 4 indicated that there was a significant relationship (P-value = 0.000) between pre- and post-training, and the correlation between them was 0.722, which showed a moderate relationship. This means the student had a good prior skill, and then after taking training, they could add skills to their prior skill in the post-training session. Table 5 showed that there was a significant mean difference between the pre- and post-training exam results. The hypothesis of the analysis was H0:μD=0 VS H0: μD≠0, Then our sig–-value (0.000), which could show us we had enough evidence to reject the null hypothesis, which is that there were the same exam scores between pre- and post-training. In this regard, we could say that there are different exam results between pre- and post-training.
Figure 5. Students age group.
Table 3. Paired sample statistics of training.

Paired Samples Test

Mean

N

Std. Deviation

Std. Error Mean

Pair 1

post training

1.9130

23

.59643

.12436

pre-training

1.1304

23

.34435

.07180
Table 4. Correlation analysis of pre- and post-training.

N

Correlation

Sig.

Pair 1

Post-training & Pre-training

23

.722

.000
Table 5. Paired sample test of pre- and post-training.

Paired Differences

Mean

Std. Deviation

SE (Mean)

95% Confidence Interval of the Difference

Lower

Upper

t

df.

Sig (2-tailed)

Pair 1 pre-post training

0.783

0.421

0.888

0.66

0.965

8.889

22

0.000
4. Conclusion
The findings of this action research highlight the significance of training in improving students' skills with SPSS statistical software. Knowledge of statistical software is essential for any data analysis in research. Before the training, students struggled with basic tasks such as opening and closing SPSS, managing data, and performing both descriptive and inferential statistics using SPSS. However, after the training, students were able to perform these tasks effectively. This improvement indicates that students' skills in using SPSS for data management and statistical analysis have increased. Consequently, students are now capable of handling both simple and complex data analyses with SPSS. Moreover, such training programs can boost students' foundational knowledge and motivation for future research endeavors. Therefore, we conclude that SPSS training is crucial for improving students' skills in using SPSS software statistical software.
Abbreviations

SPSS

Statistical Package for the Social Sciences

IBM

International Business Machines, Statistical

SPSS

Package for the Social Sciences
Acknowledgments
We extend our gratitude to Wolkite University for their invaluable support in providing the research infrastructure and essential instruments for conducting the current study.
Author Contributions
Debebe Landina Lata: Conceptualization, Methodology, Investigation and Writing-original draft.
Bontu Habtamu: Methodology, Writing-original draft, editing, Material funding, and validation.
Netsanet Mamo: Conceptualization, Methodology, Investigation and Writing-original draft.
Rahel Kedir: Methodology, Writing-original draft, editing, Material funding, and validation.
Misgana Tekle: Supervision, Data curation, Resources, Acquisition, Facilitating and validation.
Yitages Negede: Supervision, Data curation, Resources, Acquisition, Facilitating and validation.
Ethics Approval
There is no ethical problem.
Data and Code Availability
Data will be made available on request.
Funding
This work was not supported by any organizations.
Conflicts of Interest
There are no conflicts of interest to disclose regarding this current paper.
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    Lata, D. L., Habtamu, B., Mamo, N., Kedir, R., Tekle, M., et al. (2025). Enhancing SPSS Proficiency and Operational Competencies Among 4th Year Statistics Students at Wolkite University: An Action Research Study. Advances, 6(2), 73-80. https://doi.org/10.11648/j.advances.20250602.16

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    Lata, D. L.; Habtamu, B.; Mamo, N.; Kedir, R.; Tekle, M., et al. Enhancing SPSS Proficiency and Operational Competencies Among 4th Year Statistics Students at Wolkite University: An Action Research Study. Advances. 2025, 6(2), 73-80. doi: 10.11648/j.advances.20250602.16

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    AMA Style

    Lata DL, Habtamu B, Mamo N, Kedir R, Tekle M, et al. Enhancing SPSS Proficiency and Operational Competencies Among 4th Year Statistics Students at Wolkite University: An Action Research Study. Advances. 2025;6(2):73-80. doi: 10.11648/j.advances.20250602.16

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  • @article{10.11648/j.advances.20250602.16,
  author = {Debebe Landina Lata and Bontu Habtamu and Netsanet Mamo and Rahel Kedir and Misgana Tekle and Yitages Negede},
  title = {Enhancing SPSS Proficiency and Operational Competencies Among 4th Year Statistics Students at Wolkite University: An Action Research Study
},
  journal = {Advances},
  volume = {6},
  number = {2},
  pages = {73-80},
  doi = {10.11648/j.advances.20250602.16},
  url = {https://doi.org/10.11648/j.advances.20250602.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.advances.20250602.16},
  abstract = {Statistics is essential in daily life, making it crucial for educators and learners to master its use and interpretation. Statistical Package for the Social Sciences (SPSS) statistical software helps avoid mathematical errors and ensures accurate results for researchers, students, and educators. Statistical analysis is crucial for drawing meaningful conclusions in modern research across various disciplines. It also helps students present their research effectively and empowers professionals to interact with data, promoting creativity and innovation in their fields. The main objective of the research was to improve the skills of Wolkite University's fourth-year statistics students by enhancing their operational skills in statistical SPSS software. The data from the student questionnaire was tabulated and analysed using descriptive statistical methods, and the student's performance before and after the training was recorded using inferential statistics. The SPSS version 27 software was used to analysed the collected data. From the descriptive statistics of the total 23 (100%) students, the proportion of male and female students is 20 (86.96%) and 3 (13.04%), respectively. Before the training, of the total of 23 (100%) students, 19 (82.6%) had good skills, and the remaining 4 (17.4%) students had very good skills. However, 13 (56.5%) students had excellent skills after training, and the remaining 10 (43.5%) had excellent skills in SPSS software. The proposed actions for increasing the performance of students in SPSS were focused on improving basic statistical data using SPSS statistical software.
},
 year = {2025}
}

    Copy | Download 

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SN  - 2994-7200
UR  - https://doi.org/10.11648/j.advances.20250602.16
AB  - Statistics is essential in daily life, making it crucial for educators and learners to master its use and interpretation. Statistical Package for the Social Sciences (SPSS) statistical software helps avoid mathematical errors and ensures accurate results for researchers, students, and educators. Statistical analysis is crucial for drawing meaningful conclusions in modern research across various disciplines. It also helps students present their research effectively and empowers professionals to interact with data, promoting creativity and innovation in their fields. The main objective of the research was to improve the skills of Wolkite University's fourth-year statistics students by enhancing their operational skills in statistical SPSS software. The data from the student questionnaire was tabulated and analysed using descriptive statistical methods, and the student's performance before and after the training was recorded using inferential statistics. The SPSS version 27 software was used to analysed the collected data. From the descriptive statistics of the total 23 (100%) students, the proportion of male and female students is 20 (86.96%) and 3 (13.04%), respectively. Before the training, of the total of 23 (100%) students, 19 (82.6%) had good skills, and the remaining 4 (17.4%) students had very good skills. However, 13 (56.5%) students had excellent skills after training, and the remaining 10 (43.5%) had excellent skills in SPSS software. The proposed actions for increasing the performance of students in SPSS were focused on improving basic statistical data using SPSS statistical software.

VL  - 6
IS  - 2
ER  -

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Author Information

  • Debebe Landina Lata

    Department of Biotechnology, College of Natural and Computational Science, Wolkite University, Wolkite, Ethiopia

    Contact Email

    http://orcid.org/0009-0005-8402-4839

  • Bontu Habtamu

    Department of Biotechnology, College of Natural and Computational Science, Wolkite University, Wolkite, Ethiopia

  • Netsanet Mamo

    Department of Statistics, College of Natural and Computational Science, Wolkite University, Wolkite, Ethiopia

  • Rahel Kedir

    Department of Statistics, College of Natural and Computational Science, Wolkite University, Wolkite, Ethiopia

  • Misgana Tekle

    Department of Educational Planning and Management, College of Education, Wolkite University, Wolkite, Ethiopia

  • Yitages Negede

    Department of Mathematics, College of Natural and Computational Science, Wolkite University, Wolkite, Ethiopia

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