A Novel Automated Assessment Technique in e-Learning Using Short Answer Type Questions

Kar, Sadhu Prasad; Chatterjee, Rajeev; Mandal, Jyotsna Kumar

doi:10.1007/978-981-10-6427-2_12

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…We systematically developed the inclusion and exclusion criteria (Section No. Year Studies Total 1 2016 [20], [21], [11], [22], [23], [24], [12], [15] 8 2 2017 [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35] 11…”

Section: Quality Assessmentmentioning

confidence: 99%

“…3 SPRINGER [28], [14], [44], [29], [30], [58], [45], [31], 15 [63], [46], [47], [64], [32], [19], [33] 4 ACM [40], [41], [55], [12], [42], [43], [56], […”

Section: Quality Assessmentunclassified

“…35 [53], [41], [55], [42], [43], [57], [28], [14], [29], [30], [58], [45], [31], [46], [32], [19], [33], [65], [15], [66], [59], [34], [48], [35] Table 6: Leading online exam features targeted in the selected studies…”

Section: Datasetsmentioning

confidence: 99%

“…and Evaluation [43], [56], [30], [58], [63], [46], [32], [65], [66], [59] 4 Usability [57], [15] 2 5 Other [20], [13], [52], [27], [44], [29], [34], [60], [48] 9…”

Section: No Categorymentioning

confidence: 99%

“…Traditional Development [36], [21], [51], [52], [26], [27], [54], [12], [56], [44], [45], 15 [63], [64], [33], [59] 5 Additional [20], [13], [25], [50], [37], [22], [57], [28], [14], [29], [30], 17 [58], [19], [65], [15], [34], [60] [49], [38], [61], [55] 2 Face Recognition Techniques / Algorithms [13], [25], [50], [28] 3 Head Pose Estimation and Detection Techniques [11], [57], [35] 4 Natural Language Processing (NLP) Based Techniques [62], [53], [32] 5 Genetic Algorithms [43], [63], …”

Section: No Categorymentioning

confidence: 99%

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A Systematic Review of Online Exams Solutions in E-learning: Techniques, Tools and Global Adoption

Muzaffar¹,

Tahir²,

Anwar³

et al. 2020

Preprint

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E-learning in higher education is exponentially increased during the past decade due to its inevitable benefits in critical situations like natural disasters, wars, and pandemic like COVID 2019. The reliable, fair, and seamless execution of online exams in E-learning is highly significant. Particularly, online exams are conducted on E-learning platforms without the physical presence of students and instructors at the same place. This poses several issues like integrity and security during online exams. To address such issues, researchers frequently proposed different techniques and tools. However, a study summarizing and analyzing latest developments, particularly in the area of online examination, is hard to find in the literature. In this article, a Systematic Literature Review (SLR) of online examination is performed to select and analyze 53 studies published during the last five years (i.e. Jan 2016 to July 2020). Subsequently, five leading online exams features targeted in the selected studies are identified. Moreover, underlying development approaches for the implementation of online exams solutions are explored. Furthermore, 16 important techniques / algorithms and 11 datasets are presented. In addition to this, 21 online exams tools proposed in the selected studies are identified. Additionally, 25 leading existing tools used in the selected studies are also presented. Finally, the par-

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Section: Quality Assessmentmentioning

confidence: 99%

“…3 SPRINGER [28], [14], [44], [29], [30], [58], [45], [31], 15 [63], [46], [47], [64], [32], [19], [33] 4 ACM [40], [41], [55], [12], [42], [43], [56], […”

Section: Quality Assessmentunclassified

Section: Datasetsmentioning

confidence: 99%

“…and Evaluation [43], [56], [30], [58], [63], [46], [32], [65], [66], [59] 4 Usability [57], [15] 2 5 Other [20], [13], [52], [27], [44], [29], [34], [60], [48] 9…”

Section: No Categorymentioning

confidence: 99%