| Literature DB >> 35975216 |
Munish Saini1, Eshan Sengupta1, Madanjit Singh2, Harnoor Singh1, Jaswinder Singh2.
Abstract
Sustainable Development Goals (SDG) are at the forefront of government initiatives across the world. The SDGs are primarily concerned with promoting sustainable growth via ensuring wellbeing, economic growth, environmental legislation, and academic advancement. One of the most prominent goals of the SDG is to provide learners with high-quality education (SDG 4). This paper aims to look at the perspectives of the Sustainable Development Goals improvised to provide quality education. We also analyze the existing state of multiple initiatives implemented by the Indian government in the pathway to achieving objectives of quality education (SDG 4). Additionally, a case study is considered for understanding the association among the observed indicators of SDG4. For this purpose, exploratory data analysis, and numerical association rule mining in combination with QuantMiner genetic algorithm approaches have been applied. The outcomes reveal the presence of a significant degree of association among these parameters pointing out the fact that understanding the impact of one (or more) indicator on other related indicators is critical for achieving SDG 4 goals (or factors). These findings will assist governing bodies in taking preventive measures while modifying existing policies and ensuring the effective enactment of SDG 4 goals, which also will subsequently aid in the resolution of issues related to other SDGs.Entities:
Keywords: Education; Equality; Machine learning; Quality education; Right of education; Sustainable Development Goal (SDG)
Year: 2022 PMID: 35975216 PMCID: PMC9371379 DOI: 10.1007/s10639-022-11265-4
Source DB: PubMed Journal: Educ Inf Technol (Dordr) ISSN: 1360-2357
Fig. 1Sustainable Development Goals (SDG)
Fig. 2Sustainable Development Goal (SDG) 4 and its components for education
Summary of initiatives and their associations with SDG4 elements
| S. No | Name of the Initiative | Key Objectives | Associated SDG Elements |
|---|---|---|---|
| 1 | Swayam Programme | • Online training • Free Study • Equivalence with Interationational standards | SDG 4.2 SDG 4.3 SDG 4.4 |
| 2 | National E-Library | • Quality Content • Digitization • International partnerships • Online accessibility | SDG 4.2 SDG 4.4 SDG 4.5 SDG 4.1 |
| 3 | Saksham | • Help differently-abled students • Scholarships • Merit-based accommodations | SDG 4.6 SDG 4. a SDG 4. b |
| 4 | Beti Bachao Beti Padhao Abhiyan | • Women and Child development • Targetted up to 100 districts • Improve gender ratio • Special Incentives to schools promoting girls for education | SDG 4.2 SDG 4.3 SDG 4.5 SDG 4.7 |
| 5 | UDAAN | • Upbring underprivileged girl students from vulnerable positions • Promotes mathematics and science studies • Encourage girls to engineering studies • Three-dimensional focus: Curriculum design, transaction, assessment | SDG 4. a SDG 4. b SDG 4.6 |
| 6 | Pragati | • Bring girls into the technical education • Selection of at least one girl per family • Executed by the individual state government • Assist 4000 females per year | SDG 4.1 SDG 4.3 SDG 4. c SDG 4.5 |
| 7 | Ishan Uday | • Targeting students from northeast regions • Special scholarship program • More than 10,000 scholarships per year | SDG 4. a SDG 4.5 SDG 4. b |
| 8 | Ishān Vikās | • Close touch with IITs • Ten-day visit for exposure • Targeting students from northeast regions | SDG 4.1 SDG 4.2 SDG 4.4 |
Fig. 3Data analysis methodology
Indicators of Sustainable development goal for education (SDG 4)
| Indicator | SDG | Description |
|---|---|---|
| I1 | 4.1.1.C | The proportion of young people in lower secondary grades |
| I2 | 4.2.1.ger | Gross Enrollment Ratio in Organized Learning (Pre-primary and Primary) |
| I3 | 4.c. overall | Pupil Teacher Ratio |
| I4 | 4.5.1.b.gpi | Gender Parity Index |
| I5 | 4.1.1. a | The proportion of young people in pre-primary grades |
| I6 | 4.6.1. a | Proficiency level attained by a population |
| I7 | 4.1.1. ii | Mathematics proficiency in primary level |
| I8 | 4.1.1. b | Scholarship amount offered to underprivileged students |
| I9 | 4.5.3.c. secondary | Discrimination in secondary education enrollment Rate |
| I10 | 4.3.1 | Participation of youth and adults in training |
| I11 | 4.7 | Tertiary education enrollment according to GPI |
Basic outlook of the data from EDA
| Indicators | Mean | Standard Deviation | Minimum | Maximum |
|---|---|---|---|---|
| I1 | 78.45784694 | 18.45859991 | 39.45017 | 97.71132 |
| I2 | 101.9767742 | 7.607140675 | 91.5 | 110.9 |
| I3 | 30.46367742 | 7.479495364 | 19.676 | 45.5 |
| I4 | 0.744433 | 0.173974 | 0.5321 | 1.1 |
| I5 | 101.4313989 | 8.004036083 | 91.1465 | 114.53832 |
| I6 | 68.00483021 | 11.61212291 | 52.87452698 | 85.8558502 |
| I7 | 36.37709677 | 7.511266285 | 25.14 | 45.258 |
| I8 | 123,679,550.3 | 15,073,584.96 | 97,318,112 | 145,802,544 |
| I9 | 49.70714 | 21.21664 | 17 | 82.5 |
| I10 | 0.757884 | 0.184754 | 0.520219982 | 1.10283 |
| I11 | 1.09262 | 0.053237 | 0.95002001 | 1.168255 |
Fig. 4Box plot extracted from the analysis of the dataset
Correlation matrix
| I1 | I2 | I3 | I4 | I5 | I6 | I7 | I8 | I9 | I10 | I11 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| I1 | 1 | 0.886103 | -0.74864 | 0.764607 | 0.824801 | 0.688844 | -0.63196 | 0.903865 | -0.80362 | 0.777612 | 0.40657 |
| I2 | 0.886103 | 1 | -0.6976 | 0.748999 | 0.914259 | 0.768446 | -0.74718 | 0.928251 | -0.82161 | 0.769451 | 0.565291 |
| I3 | -0.74864 | -0.6976 | 1 | -0.5537 | -0.56339 | -0.33934 | 0.307793 | -0.64811 | 0.553802 | -0.55896 | -0.47555 |
| I4 | 0.764607 | 0.748999 | -0.5537 | 1 | 0.580915 | 0.858876 | -0.84286 | 0.645293 | -0.94995 | 0.994068 | 0.567998 |
| I5 | 0.824801 | 0.914259 | -0.56339 | 0.580915 | 1 | 0.651673 | -0.64426 | 0.982081 | -0.6982 | 0.606054 | 0.451884 |
| I6 | 0.688844 | 0.768446 | -0.33934 | 0.858876 | 0.651673 | 1 | -0.94636 | 0.669437 | -0.92939 | 0.881908 | 0.446669 |
| I7 | -0.63196 | -0.74718 | 0.307793 | -0.84286 | -0.64426 | -0.94636 | 1 | -0.64849 | 0.911427 | -0.86662 | -0.51257 |
| I8 | 0.903865 | 0.928251 | -0.64811 | 0.645293 | 0.982081 | 0.669437 | -0.64849 | 1 | -0.74808 | 0.670839 | 0.460511 |
| I9 | -0.80362 | -0.82161 | 0.553802 | -0.94995 | -0.6982 | -0.92939 | 0.911427 | -0.74808 | 1 | -0.97007 | -0.55927 |
| I10 | 0.777612 | 0.769451 | -0.55896 | 0.994068 | 0.606054 | 0.881908 | -0.86662 | 0.670839 | -0.97007 | 1 | 0.576854 |
| I11 | 0.40657 | 0.565291 | -0.47555 | 0.567998 | 0.451884 | 0.446669 | -0.51257 | 0.460511 | -0.55927 | 0.576854 | 1 |
Pearson correlation coefficient
| Correlation Coefficient Value | Indication |
|---|---|
| 1 ≥ r ≥ 0.60 | High Correlation |
| 0.60 ≥ r ≥ 0.30 | Moderate Correlation |
| 0.30 ≥ r ≥ -0.50 | Low Correlation |
| -0.50 ≥ r ≥ -0.90 | Negligible Correlation |
Perfromance measures and number of association rules
| Support (%) | Confidence (%) | Number of Rules |
|---|---|---|
| 50 – 60 | 100 | 4052 |
| 60 – 70 | 100 | 2878 |
| 70 – 80 | 100 | 206 |
| 80 – 90 | 100 | 153 |
| 90 – 100 | 100 | 60 |
Fig. 5Visualization of rules with a support rate between 90 to 100%