Abbas, A. R., & Farooq, A. O. (2019). Skin Detection using ImprovedID3 Algorithm. Iraqi Journal of Science, 402-410.
Adnan, M., Sarno, R., & Sungkono, K. R. (2019, September). Sentimentanalysis of restaurant review with classification approach in thedecision tree-j48 algorithm. In 2019 International Seminar onApplication for Technology of Information and Communication(iSemantic) (pp. 121-126). IEEE.
Alhassan, A., & Ali, H. (2020). Towards a multisource performanceappraisal model in Omani higher education institutions. ArabWorld English Journal (AWEJ) Volume, 10.
Almutairi, T. S., & Shraid, N. S. (2021). Teacher Evaluation by DifferentInternal Evaluators: Head of Departments, Teachers Themselves,Peers and Students. International Journal of Evaluation andResearch in Education, 10(2), 588-596.
Alshamsi, A., Bayari, R., & Salloum, S. (2020). Sentiment analysis inEnglish texts. Advances in Science, Technology and EngineeringSystems Journal, 5(6), 1683-1689.
Alzanin, S. M., & Azmi, A. M. (2019). Rumor detection in Arabic tweetsusing semi-supervised and unsupervised expectation–maximization. Knowledge-Based Systems, 185, 104945.
Baluyos, G. R., Rivera, H. L., & Baluyos, E. L. (2019). Teachers’ jobsatisfaction and work performance. Open Journal of SocialSciences, 7(08), 206.
Bal-Tastan, S., Davoudi, S. M. M., Masalimova, A. R., Bersanov, A. S.,Kurbanov, R. A., Boiarchuk, A. V., & Pavlushin, A. A. (2018).The impacts of teacher’s efficacy and motivation on student’sacademic achievement in science education among secondary andhigh school students. EURASIA Journal of Mathematics, Scienceand Technology Education, 14(6), 2353-2366.
Bardack, S., & Obradovi?, J. (2019). Observing teachers’ displays andscaffolding of executive functioning in the classroomcontext. Journal of Applied Developmental Psychology, 62, 205-219.
Bradford, C., & Braaten, M. (2018). Teacher evaluation and thedemoralization of teachers. Teaching and Teacher Education, 75,49-59.
Buchanan, J., Harb, G., & Fitzgerald, T. (2020). Implementing a TeachingPerformance Assessment: An Australian Case Study. AustralianJournal of Teacher Education, 45(5), 74-90.
Carlucci, D., Renna, P., Izzo, C., & Schiuma, G. (2019). Assessingteaching performance in higher education: a framework forcontinuous improvement. Management Decision.
Caroro, R. A., Sison, A. M., & Medina, R. P. (2018). An EnhancedFrequent Pattern-Growth Algorithm with Dual Pruning usingModified Anti-Monotone Support. In 2018 IEEE 10thInternational Conference on Humanoid, Nanotechnology,Information Technology, Communication and Control,Environment and Management (HNICEM) (pp. 1-5). IEEE.
Caroro, R. A., Sison, A. M., & Medina, R. P. (2019, January). ModifiedAnti-Monotone Support Pruning on FP Tree for ImprovedFrequent Pattern Generation. In Proceedings of the 2ndInternational Conference on Software Engineering andInformation Management (pp. 138-142).
Clayson, D. E. (2018). Student evaluation of teaching and matters ofreliability. Assessment & Evaluation in Higher Education, 43(4),666-681.
Derrington, M. L., & Campbell, J. W. (2018). Teacher evaluation policytools: Principals’ selective use in instructionalleadership. Leadership and Policy in Schools, 17(4), 568-590.
De Silva, S., Dayarathna, S., Ariyarathne, G., Meedeniya, D., Jayarathna,S., Michalek, A. M., & Jayawardena, G. (2019, July). A rule-basedsystem for ADHD identification using eye movement data.In 2019 Moratuwa Engineering Research Conference(MERCon) (pp. 538-543). IEEE.
Gálvez Suarez, E., & Milla Toro, R. (2018). Teaching PerformanceEvaluation Model: Preparation for Student Learning within theFramework for Teacher Good Performance. Journal ofEducational Psychology-Propositos y Representaciones, 6(2),431-452.
Guillén-Gámez, F. D., & Mayorga-Fernández, M. J. (2020). Identificationof variables that predict teachers’ attitudes toward ICT in highereducation for teaching and research: A study withregression. Sustainability, 12(4), 1312.
Hiver, P., Solarte, A. C. S., Whiteside, Z., Kim, C. J., & Whitehead, G. E.(2021). The role of language teacher metacognition and executivefunction in exemplary classroom practice. The Modern LanguageJournal, 105(2), 484-506.
Holland, P. E. (2020). Standards for teacher evaluation. In Standards forInstructional (pp. 139-153). Routledge.
Huang, X., Huang, X., & Wang, X. (2021). Construction of the teachingquality monitoring system of physical education courses incolleges and universities based on the construction of smartcampus with artificial intelligence. Mathematical Problems inEngineering, 2021.
Jalota, C., & Agrawal, R. (2019, February). Analysis of educational datamining using classification. In 2019 International Conference onMachine Learning, Big Data, Cloud and Parallel Computing(COMITCon) (pp. 243-247). IEEE.
Kausar, S., Huahu, X., Hussain, I., Wenhao, Z., & Zahid, M. (2018).Integration of data mining clustering approach in the personalizedE-learning system. IEEE Access, 6, 72724-72734.
Keenan, L., O’Sullivan, A., & Downes, M. (2021). Teachers’ experiencesand understanding of executive functions in Irish primary schoolclassrooms: Findings from a mixed-methods questionnaire. IrishEducational Studies, 40(1), 101-114.
Klassen, R. M., & Kim, L. E. (2019). Selecting teachers and prospectiveteachers: A meta-analysis. Educational Research Review, 26, 32-51.
Kusumaningrum, D. E., Sumarsono, R. B., & Gunawan, I. (2019).Professional ethics and teacher teaching performance:Measurement of teacher empowerment with a soft systemmethodology approach. International Journal of Innovation,Creativity and Change, 5(4), 611-624.
Lee, J. S. (2019). AUC4. 5: AUC-based C4. 5 decision tree algorithm forimbalanced data classification. IEEE Access, 7, 106034-106042.
Lumasag, J. M., Talirongan, H., Talirongan, F. J. B., & Labanza, C. L.(2020). Data-driven Decision Support on Student’s Behaviorusing Fuzzy-Based Approach. Middle East Journal of AppliedScience & Technology, 3(4), 59-68.
Moreno, M. L. (2020). Empirical research on multisource feedback inperformance appraisal processes: A systematic literaturereview (Doctoral dissertation, Universidade de Coimbra).
Novitasari, D., Asbari, M., Purwanto, A., Fahmalatif, F., Sudargini, Y.,Hidayati, L. H., & Wiratama, J. (2021). The Influence of SocialSupport Factors on Performance: A Case Study of ElementarySchool Teachers. International Journal of Social andManagement Studies, 2(1), 41-52.
Orong, M. Y., Sison, A. M., & Hernandez, A. A. (2018, May). Mitigatingvulnerabilities through forecasting and crime trend analysis.In 2018 5th International Conference on Business and IndustrialResearch (ICBIR) (pp. 57-62). IEEE.
Pan, G., Shankararaman, V., Koh, K., & Gan, S. (2021). Students’evaluation of teaching in the project-based learning programme:An instrument and a development process. The InternationalJournal of Management Education, 19(2), 100501.
Paredes, R. K., Fajardo, A. C., & Sison, A. M. (2018, November). Afuzzy-based dynamic bandwidth allocation approach for campusarea networks. In 2018 IEEE 5th International Conference onEngineering Technologies and Applied Sciences (ICETAS) (pp. 1-6). IEEE.
Qiang, G., Sun, L., & Huang, Q. (2020, April). ID3 algorithm and itsimproved algorithm in agricultural planting decision. In IOPConference Series: Earth and Environmental Science (Vol. 474,No. 3, p. 032025). IOP Publishing.
Rady, E. H. A., & Anwar, A. S. (2019). Prediction of kidney diseasestages using data mining algorithms. Informatics in MedicineUnlocked, 15, 100178.
Raman, R., & Nedungadi, P. (2020). Adoption of web-enabled studentevaluation of teaching (WESET). International Journal ofEmerging Technologies in Learning (IJET), 15(24), 191-207.
Raju, S. S., & Dhandayudam, P. (2018, April). Prediction of customerbehaviour analysis using classification algorithms. In AIPconference proceedings (Vol. 1952, No. 1, p. 020098). AIPPublishing LLC.
Reddy, G. S., & Chittineni, S. (2021). Entropy based C4. 5-SHOalgorithm with information gain optimization in datamining. PeerJ Computer Science, 7, e424.
Renata, R., Wardiah, D., & Kristiawan, M. (2018). The influence ofheadmaster’s supervision and achievement motivation oneffective teachers. International Journal of Scientific &Technology Research, 7(4), 44-49.
Retnowati, T. H., Mardapi, D., Kartowagiran, B., & Hamdi, S. (2021). AModel of Lecturer Performance Evaluation: Sustainable LecturerPerformance Mapping. International Journal ofInstruction, 14(2), 83-102.
Sammaknejad, N., Zhao, Y., & Huang, B. (2019). A review of theexpectation maximization algorithm in data-driven processidentification. Journal of process control, 73, 123-136.
Sang, X., Guo, Q., Wu, X., Fu, Y., Xie, T., He, C., & Zang, J. (2019).Intensity and stationarity analysis of land use change based onCART algorithm. Scientific reports, 9(1), 1-12.
Soto-Pérez, M., Sánchez-García, J. Y., & Núñez-Ríos, J. E. (2020).Factors to improve job performance and schooleffectiveness. International Journal of EducationalManagement, 34(5), 805-822.
Souri, A., & Hosseini, R. (2018). A state-of-the-art survey of malwaredetection approaches using data mining techniques. Human-centric Computing and Information Sciences, 8(1), 1-22.
Sugiyarti, E., Jasmi, K. A., Basiron, B., Huda, M., Shankar, K., &Maseleno, A. (2018). Decision support system of scholarshipgrantee selection using data mining. International Journal of Pureand Applied Mathematics, 119(15), 2239-2249.
Susanto, R., Agustina, N., Azmi, Y., & Rachbini, W. (2021). PedagogicCompetency Model: Development from The Point of View of TheInitial Characteristics of Teachers, Involvement withOrganizations and Competency Development Strategies. Reviewof International Geographical Education Online, 11(8), 826-841.
Thibaut, L., Knipprath, H., Dehaene, W., & Depaepe, F. (2018). Theinfluence of teachers’ attitudes and school context on instructionalpractices in integrated STEM education. Teaching and teachereducation, 71, 190-205.
Van Leeuwen, A., & Janssen, J. (2019). A systematic review of teacherguidance during collaborative learning in primary and secondaryeducation. Educational Research Review, 27, 71-89.
Wasserman, E., & Migdal, R. (2019). Professional Development:Teachers' Attitudes in Online and Traditional TrainingCourses. Online Learning, 23(1), 132-143.
Wentworth, D. K., Behson, S. J., & Kelley, C. L. (2020). Implementing anew student evaluation of teaching system using the Kotter changemodel. Studies in Higher Education, 45(3), 511-523.
Wu, Y., Lian, K., Hong, P., Liu, S., Lin, R. M., & Lian, R. (2019).Teachers’ emotional intelligence and self-efficacy: Mediating roleof teaching performance. Social Behavior and Personality: aninternational journal, 47(3), 1-10.
Xu, X., Wang, Y., & Yu, S. (2018). Teaching performance evaluation insmart campus. IEEE Access, 6, 77754-77766.
Yang, S., Guo, J. Z., & Jin, J. W. (2018). An improved Id3 algorithm formedical data classification. Computers & ElectricalEngineering, 65, 474-487.
Yang, F. J. (2019, December). An extended idea about decision trees.In 2019 International Conference on Computational Science andComputational Intelligence (CSCI) (pp. 349-354). IEEE.