# Examining the Optimal Choice of SEM Statistical Software Packages for Sustainable Mathematics Education: A Systematic Review

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## Abstract

**:**

## 1. Introduction

- RQ: What are the optimal choices of proprietary statistical software packages in SEM approaches for sustainable mathematics education?

## 2. Methodology

#### 2.1. The Review Protocol (PRISMA)

#### 2.2. Resources

#### 2.3. Systematic Review Process

#### 2.3.1. Identification

#### 2.3.2. Screening

#### 2.3.3. Eligibility

#### 2.3.4. Inclusion Criteria

#### 2.4. Data Abstraction and Analysis

## 3. Results

#### 3.1. General Findings

#### 3.1.1. Distribution of Publications Based on Countries

#### 3.1.2. Distribution of Publications Based on Years

#### 3.1.3. Distribution of Publications Based on Research Design

#### 3.1.4. Distribution of Publications Based on Samples

#### 3.2. Main Findings

#### 3.2.1. CB-SEM Statistical Applications

#### 3.2.2. VB-SEM/PLS-SEM Statistical Applications

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Study flow diagram (adapted from [58]).

Database | Keywords Used |
---|---|

Scopus | TITLE-ABS-KEY ([“structural equation modeling” OR “SEM”] AND [“covariance-based SEM” OR “CB-SEM” OR “variance-based SEM” OR “VB-SEM” OR “partial least square” OR “partial least square-SEM” OR “partial least square structural equation modeling” OR “PLS-SEM” OR “proprietary statistical software package*” OR “statistical application*” OR “statistical program*” OR “statistical software*” OR “SEM software*” OR “software package*” OR “software program”*] AND [“mathematic*” OR “mathematic* education” OR “mathematic* teach* and learning” OR “mathematic* literacy” OR “mathematic* subject” OR “mathematic* discipline”]) |

Criterion (C) | Inclusion (I) | Exclusion (E) |
---|---|---|

Type of article/literature | Journal (research articles/empirical articles) | Journals (systematic review/non-empirical articles), book series, chapter in book, and conference proceeding |

Language | English | Non-English |

Timeline | Between 2018 and 2022 | <2018 |

Country/region | All | - |

Field | Mathematics education/subject/discipline/literacy/TnL | Non-mathematics education/subject/discipline/literacy/TnL |

**Table 3.**The findings regarding the types of proprietary statistical software packages according to SEM approaches.

No | Study | Research Design | Countries | Sample and Level | Types of Proprietary Statistical Software Packages According to SEM Approaches | |||||
---|---|---|---|---|---|---|---|---|---|---|

CB-SEM | VB-SEM/PLS-SEM | |||||||||

Lisrel | Amos | Mplus | SmartPLS | R Package | WarpPLS | |||||

1 | [71] | QN | Malaysia | Students (International secondary school) | X | X | X | √ | X | X |

2 | [72] | QN | Malaysia | Students (International secondary school) | X | X | X | √ | X | X |

3 | [73] | QN | Malaysia | Students (International secondary school) | X | X | X | √ | X | X |

4 | [80] | QN | West Africa | Core and elective mathematics teachers (Secondary school) | X | √ | X | X | X | X |

5 | [81] | QN | West Africa | Undergraduate students (University) | X | √ | X | X | X | X |

6 | [82] | QN | West Africa | Undergraduate students (University) | X | √ | X | X | X | X |

7 | [83] | QN | West Africa | Senior students (High school) | X | √ | X | X | X | X |

8 | [84] | QN | UEA | Parents, Mathematics teachers, and students (Elementary school) | √ | X | X | X | X | X |

9 | [85] | QN | Turkey | Prospective mathematics teachers (University) | X | X | X | √ | X | X |

10 | [86] | QN | Philippines | Mathematics teachers (High school) | X | X | X | X | X | √ |

11 | [87] | QN | Taiwan | Students (Vocational high school) | X | X | X | √ | X | X |

12 | [88] | QN | Malaysia | Mathematics teachers (Secondary school) | X | X | X | √ | X | X |

13 | [89] | QN | Malaysia | Students (Secondary school) | X | X | X | √ | X | X |

14 | [90] | QN | Indonesia | Students (University) | √ | X | X | X | X | X |

15 | [91] | QN | Indonesia | Students (University) | X | √ | X | X | X | X |

16 | [92] | QN | Indonesia | Students (University) | X | √ | X | X | X | X |

17 | [93] | QN | Indonesia | Students (University) | X | √ | X | X | X | X |

18 | [94] | QN | South Korea | Students (Elementary school) | X | X | √ | X | X | X |

19 | [95] | QN | (Cyprus) Southeast Europe | Students (Primary school) | X | X | X | √ | X | X |

20 | [74] | QN | Spain | Pre-service mathematics teachers (University) | X | X | X | √ | X | X |

21 | [96] | QN | Australia | Students (University) | X | X | X | √ | X | X |

22 | [97] | QN | (Cyprus) Southeast Europe | Principal, Mathematics teachers, and students (Primary school) | X | √ | X | X | X | X |

23 | [75] | QN | India | Undergraduate students (University) | X | X | X | √ | X | X |

24 | [98] | MM | East Africa | Students (Secondary school) | X | X | √ | X | X | X |

25 | [99] | QN | Indonesia | Students (University) | √ | X | X | X | X | X |

26 | [100] | MM | USA | Students (Elementary school, charter school, and home-school groups) | X | X | √ | X | X | X |

27 | [101] | QN | Indonesia | Mathematics teachers (Secondary school) | X | X | X | √ | X | X |

28 | [102] | QN | Malaysia | Undergraduate students (University) | X | X | X | √ | X | X |

29 | [103] | QN | Malaysia | Graduate mathematics teachers (University) | X | X | X | √ | X | X |

30 | [104] | QN | Malaysia | Undergraduate students (University) | X | X | X | √ | X | X |

31 | [105] | QN | Malaysia | Undergraduate students (University) | X | X | X | √ | X | X |

32 | [106] | QN | East Africa | Students (Lower secondary school) | X | X | √ | X | X | X |

33 | [107] | QN | Southern and central Finland | Students (Lower and upper secondary school) | X | X | √ | X | √ | X |

34 | [76] | QN | West Africa | Mathematics teachers (Secondary school) | X | X | X | √ | X | X |

35 | [108] | QN | Israel | Principals, mathematics teachers, and students (Middle school) | X | X | √ | X | X | X |

36 | [109] | QN | South Africa | Students (Public university) | X | √ | X | X | X | X |

37 | [110] | QN | Malaysia | Students (Primary school) | X | X | X | √ | X | X |

38 | [111] | QN | Indonesia | Students (Secondary school) | √ | X | X | X | X | X |

39 | [112] | QN | Switzerland | Students (Primary and secondary school) | X | X | √ | X | X | X |

40 | [113] | QN | Malaysia | Students (Private high school) | X | X | X | √ | X | X |

41 | [114] | QN | Malaysia | Students (Private high school) | X | X | X | √ | X | X |

42 | [115] | QN | Malaysia | Students (Private lower-level high school) | X | X | X | √ | X | X |

43 | [116] | QN | Spain | Undergraduate students (University) | X | X | X | √ | X | X |

44 | [117] | QN | East Africa | Mathematics teachers (Secondary school) | X | √ | X | X | X | X |

45 | [118] | QN | Indonesia | Mathematics teachers (Secondary school) | X | X | X | √ | X | X |

46 | [119] | QN | China | Students (University) | X | √ | X | X | X | X |

47 | [120] | QN | USA | Mathematics teachers and students (Middle school) | X | X | X | X | X | √ |

Study | CB-SEM Statistical Applications |
---|---|

[84,90,99,111] | Lisrel (N = 4 studies) |

[80,81,82,83,91,92,93,97,109,117,119] | Amos (N = 11 studies) |

[94,98,100,106,107,108,112] | Mplus (N = 7 studies) |

Study | VB-SEM/PLS-SEM Statistical Applications |
---|---|

[71,72,73,74,75,76,85,87,88,89,95,96,101,102,103,104,105,110,113,114,115,116,118] | SmartPLS (N = 23 studies) |

[107] | R package (plspm) (N = 1 study) |

[86,120] | WarpPLS (N = 2 studies) |

Study | Findings |
---|---|

[71] | F1: a significant relationship between performance expectancy, effort expectancy, and student attitude toward the use of an online mathematics homework tool. F2: a significant relationship between student attitudes and their actual use of online homework. |

[72] | F1: a significant relationship between perceived usefulness, perceived ease of use, and attitude toward the use of a web-based mathematics homework tool. F2: a significant relationship between attitude and mathematics self-efficacy factor. |

[73] | F1: perceived usefulness and perceived ease of use are predictors of attitude toward the use of OHW. |

[85] | F1: direct effects of technological content knowledge (TCK), technological pedagogical knowledge (TPK21), and pedagogical content knowledge (PCK21) on TPACK-21. F2: teachers’ content knowledge (CK), technological knowledge (TK), and pedagogical knowledge (PK21) directly affect technological content knowledge (TCK). |

[87] | F1: perceived usefulness significantly affected attitude toward use and behavioral intention to use. F2: attitude toward use significantly affected behavioral intention to use. F3: attitude toward use exhibited significant mediating effects between perceived usefulness and behavioral intention to use. |

[88] | F1: infrastructure support and system quality affect teachers’ intention to use geometer’s sketchpad. |

[89] | F1: teacher affective support and classroom instruction predict attitude towards mathematics more than parental influences. |

[95] | F1: the mathematical mindset of students could directly and moderately describe their mathematical knowledge. F2: mathematical knowledge and mathematical mindset can both directly and to a significant extent be used to describe mathematical imagination. |

[74] | F1: component relation effects of OB, ATP, and ATN of pre-service teachers toward mathematics learning and the influence of their educational background. F2: science and technology background were positively correlated after the flipped-OCN method compared with the rest of pre-service teachers. |

[96] | F1: a significant relationship between students’ self-efficacy, self-regulated learning strategies, and epistemological beliefs about mathematics as well as their perceptions of the learning environment. |

[75] | F1: learning through constructivist Digital Learning Heutagogy supported academic achievement, learning engagement, and positive emotions F2: peer relationship not supported by the intervention. |

[101] | F1: attitude toward E-learning use and E-learning experience were the two most significant constructs in predicting E-learning use. |

[102] | F1: a significant relationship between teaching quality and students’ academic performance. |

[103] | F1: a significant relationship between Program Education Objectives (PEOs) and Program Learning Outcomes (PLOs). |

[104] | F1: a significant relationship between statistical reasoning and students’ academic performance. |

[105] | F1: students’ attitude and belief toward statistics, statistical reasoning, self-efficacy, motivation, and the relationship with academic performance are statistically important. |

[76] | F1: a significant relationship between the will, skill, tool, and pedagogy parameters and the stages of adoption of teachers’ use of ICT. F2: Tool strongly predicts ICT integration. |

[110] | F1: a significant relationship between cognitive factors (symbol sense, pattern sense, number sense, and operation sense) and algebraic thinking. |

[113] | F1: task value and critical thinking skills predicts students’ performance in mathematical reasoning. F2: critical thinking skills fully mediated with the relationship of mastery goal orientation on the students’ abilities to solve the reasoning tasks. |

[114] | F1: students’ formative performance predicts their summative performance. F2: formative performance significantly mediates the relationship between self-confidence and summative performance. |

[115] | F1: behavioral regulations (self-observation, self-judgment, and self-reaction) significantly influence student academic achievement and mathematical reasoning ability. F2: cognition regulation significantly mediates the relationship between motivational regulation and reasoning ability. F3: behavioral, cognition regulation, and students’ reasoning ability significantly mediates the relationship between motivational regulation and academic achievement. |

[116] | F1: Format and depth of the video tutorials predict performance learning and promoting autonomy. |

[118] | F1: a significant relationship between perceived ease of use and subjective norm influence (PEU and SN) with teachers’ microgame usage behaviors and intentions. |

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**MDPI and ACS Style**

Sakaria, D.; Maat, S.M.; Mohd Matore, M.E.E.
Examining the Optimal Choice of SEM Statistical Software Packages for Sustainable Mathematics Education: A Systematic Review. *Sustainability* **2023**, *15*, 3209.
https://doi.org/10.3390/su15043209

**AMA Style**

Sakaria D, Maat SM, Mohd Matore MEE.
Examining the Optimal Choice of SEM Statistical Software Packages for Sustainable Mathematics Education: A Systematic Review. *Sustainability*. 2023; 15(4):3209.
https://doi.org/10.3390/su15043209

**Chicago/Turabian Style**

Sakaria, Darmaraj, Siti Mistima Maat, and Mohd Effendi Ewan Mohd Matore.
2023. "Examining the Optimal Choice of SEM Statistical Software Packages for Sustainable Mathematics Education: A Systematic Review" *Sustainability* 15, no. 4: 3209.
https://doi.org/10.3390/su15043209