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ORCIDMohammed F. Farghally
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2020 – today
- 2024
[j5]Naglaa Abdelhady, Taysir Hassan A. Soliman, Mohammed F. Farghally:
Stacked-CNN-BiLSTM-COVID: an effective stacked ensemble deep learning framework for sentiment analysis of Arabic COVID-19 tweets. J. Cloud Comput. 13(1): 85 (2024)- [c10]Sara Hooshangi
, Asma Shakil, Subhasish Dasgupta, Karen C. Davis, Mohammed Farghally, KellyAnn Fitzpatrick, Mirela Gutica, Ryan Hardt, Ellie Lovellette, Steve Riddle, Mohammed Seyam:
Experiences of Instructors Who Teach Capstone Courses in Computing Fields. ITiCSE (2) 2024 - [c9]Mohammed F. Farghally, Mohammed Seyam, Cliff A. Shaffer:
Towards Establishing a Training Program to Support Future CS Teaching-focused Faculty. SIGCSE (1) 2024: 338-344 - 2023
- [j4]Naglaa Abdelhady, Ibrahim E. El-Semman, Mohammed F. Farghally, Taysir Hassan A. Soliman:
Developing Analytical Tools for Arabic Sentiment Analysis of COVID-19 Data. Algorithms 16(7): 318 (2023) - [c8]Samnyeong Heo, Mohammed F. Farghally, Mostafa Mohammed, Clifford A. Shaffer:
Analyzing Student Session Data in an eTextbook. iTextbooks@AIED 2023: 3-14 - [c7]Quintin I. Cutts, Maria Kallia, Ruth Anderson, Tom Crick, Marie Devlin, Mohammed Farghally, Claudio Mirolo, Ragnhild Kobro Runde, Otto Seppälä, Jaime Urquiza-Fuentes, Jan Vahrenhold:
Arguments for and Approaches to Computing Education in Undergraduate Computer Science Programmes. ITiCSE-WGR 2023: 160-195 - [c6]Quintin I. Cutts, Maria Kallia, Ruth Anderson, Tom Crick, Marie Devlin, Mohammed Farghally, Claudio Mirolo, Ragnhild Kobro Runde, Otto Seppälä, Jaime Urquiza-Fuentes, Jan Vahrenhold:
Considering Computing Education in Undergraduate Computer Science Programmes. ITiCSE (2) 2023: 567-568 - 2022
- [i2]Ahmed Abd Elrahman, Taysir Hassan A. Soliman, Ahmed I. Taloba, Mohammed F. Farghally:
A Predictive Model for Student Performance in Classrooms Using Student Interactions With an eTextbook. CoRR abs/2203.03713 (2022) - [i1]Ahmed Abd Elrahman, Taysir Hassan A. Soliman, Mohammed F. Farghally, Ahmed I. Taloba:
Evaluation of the Quality of Exercises for the Data Structures' eTextbook and Find the Difficult Topics Using Item Response Theory and Logged Data Analysis. CoRR abs/2210.05294 (2022) - 2021
- [j3]Soha Abd El-Moamen Mohamed, Marghany Hassan Mohamed, Mohammed F. Farghally:
A New Cascade-Correlation Growing Deep Learning Neural Network Algorithm. Algorithms 14(5): 158 (2021) - [c5]Mohammed F. Farghally, Mostafa Mohammed, Hamdy F. F. Mahmoud, Margaret Ellis, Derek Haqq, Molly Domino, Brett Jones, Clifford A. Shaffer:
The Online Transition of Two CS Courses in Response to COVID-19. SIGCSE 2021: 1251
2010 – 2019
- 2018
- [j2]Kyu Han Koh, Eric Fouh, Mohammed F. Farghally, Hossameldin Shahin, Clifford A. Shaffer:
Experience: Learner Analytics Data Quality for an eTextbook System. ACM J. Data Inf. Qual. 9(2): 10:1-10:10 (2018) - 2017
- [c4]Mohammed F. Farghally, Kyu Han Koh, Hossameldin Shahin, Clifford A. Shaffer:
Evaluating the Effectiveness of Algorithm Analysis Visualizations. SIGCSE 2017: 201-206 - [c3]Mohammed F. Farghally, Kyu Han Koh, Jeremy V. Ernst, Clifford A. Shaffer:
Towards a Concept Inventory for Algorithm Analysis Topics. SIGCSE 2017: 207-212 - 2016
- [c2]Eric Fouh, Mohammed F. Farghally, Sally Hamouda, Kyu Han Koh, Clifford A. Shaffer:
Investigating Difficult Topics in a Data Structures Course Using Item Response Theory and Logged Data Analysis. EDM 2016: 370-375 - [c1]Mohammed F. Farghally, Eric Fouh, Sally Hamouda, Kyu Han Koh, Clifford A. Shaffer:
Visualizing Algorithm Analysis Topics (Abstract Only). SIGCSE 2016: 687 - 2014
- [j1]Eric Fouh, Daniel A. Breakiron, Sally Hamouda, Mohammed F. Farghally, Clifford A. Shaffer:
Exploring students learning behavior with an interactive etextbook in computer science courses. Comput. Hum. Behav. 41: 478-485 (2014)
Coauthor Index
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last updated on 2024-08-05 21:18 CEST by the dblp team
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