Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Predicting and Improving Performance on Introductory Programming Courses (CS1)

This thesis describes a longitudinal study on factors which predict academic success in introductory programming at undergraduate level, including the development of these factors into a fully automated web based system (which predicts students who are at risk of not succeeding early in the introductory programming module) and interventions to address attrition rates on introductory programming courses (CS1). Numerous studies have developed models for predicting success in CS1, however there is little evidence on their ability to generalise or on their use beyond early investigations. In addition, they are seldom followed up with interventions, after struggling students have been identified. The approach overcomes this by providing a web-based real time system, with a prediction model at its core that has been longitudinally developed and revalidated, with recommendations for interventions which educators could implement to support struggling students that have been identified. This thesis makes five fundamental contributions. The first is a revalidation of a prediction model named PreSS. The second contribution is the development of a web-based, real time implementation of the PreSS model, named PreSS#. The third contribution is a large longitudinal, multi-variate, multi-institutional study identifying predictors of performance and analysing machine learning techniques (including deep learning and convolutional neural networks) to further develop the PreSS model. This resulted in a prediction model with approximately 71% accuracy, and over 80% sensitivity, using data from 11 institutions with a sample size of 692 students. The fourth contribution is a study on insights on gender differences in CS1; identifying psychological, background, and performance differences between male and female students to better inform the prediction model and the interventions. The final, fifth contribution, is the development of two interventions that can be implemented early in CS1, once identified by PreSS# to potentially improve student outcomes. The work described in this thesis builds substantially on earlier work, providing valid and reliable insights on gender differences, potential interventions to improve performance and an unsurpassed, generalizable prediction model, developed into a real time web-based system

CS1: how will they do? How can we help? A decade of research and practice

Background and Context: Computer Science attrition rates (in the western world) are very concerning, with a large number of students failing to progress each year. It is well acknowledged that a significant factor of this attrition, is the students’ difficulty to master the introductory programming module, often referred to as CS1. Objective: The objective of this article is to describe the evolution of a prediction model named PreSS (Predict Student Success) over a 13-year period (2005–2018). Method: This article ties together, the PreSS prediction model; pilot studies; a longitudinal, multi-institutional re-validation and replication study; improvements to the model since its inception; and interventions to reduce attrition rates. Findings: The outcome of this body of work is an end-to-end real-time web-based tool (PreSS#), which can predict student success early in an introductory programming module (CS1), with an accuracy of 71%. This tool is enhanced with interventions that were developed in conjunction with PreSS#, which improved student performance in CS1. Implications: This work contributes significantly to the computer science education (CSEd) community and the ITiCSE 2015 working group’s call (in particular the second grand challenge), by re-validating and developing further the original PreSS model, 13 years after it was developed, on a modern, disparate, multi-institutional data set

A molecular and cellular characterisation of the effects of neonicotinoid pesticides on the brain of the pollinator Bombus terrestris.

Bombus terrestris (L.) is one of the most important native and commercial pollinator species worldwide. Along with other pollinators their populations are in decline due to a multifactorial phenomenon that includes the extensive use of neonicotinoid insecticides. Thus, the characterisation and understanding of neonicotinoid effects on bees at the molecular level is essential to mitigate the risks of their use in the environment. This study initially characterised the brain proteomes of bumblebees in response to aging prior to assessing changes at the behavioural, cellular and molecular level as a response to neonicotinoid exposure. We demonstrated the highly catalytic nature of the developing bumblebee brain and how energy and carbohydrate metabolism increase in response to aging, while genetic information processes are downregulated. By considering differences in mode of action and mode of exposure to the neonicotinoids clothianidin and imidacloprid, the effects of acute and chronic oral exposure on bumblebee workers were determined. Neonicotinoids differentially impair energy metabolism and structural processes in the brain suggesting possible divergence of insecticide mode of action. Clothianidin and imidacloprid triggered different behavioural responses and toxicity in bees, with the former causing hyperactivity and the latter, temporal paralysis. Imidacloprid is less toxic to bumblebees and the brain physiology is differentially affected depending on chemical, dose or mode of exposure selected. The levels of the synapse associated protein synapsin increased in bumblebee brains for imidacloprid-exposed bees only, and functional annotation analysis of differential expressed proteins indicated impairment of intracellular transport, energy metabolism, translational activity, purines and pyrimidines metabolism, endocytic and exocytic activity and synaptic functioning as a whole. The pathways affected by neonicotinoid exposure vary depending on chemical and mode of exposure, which complicates the identification of biomarkers of neonicotinoid exposure in bumblebees. In addition, neonicotinoid metabolism in bees is poorly understood and these chemicals can accumulate in the bee body, which potentially contributes to long term toxicity. Overall the results presented in this thesis demonstrate individual and distinct ways by which neonicotinoids influence neuronal communication and provide novel insights into molecular aspects of bee health, through highlighting the pathways affected by aging and pesticide use on this important pollinator species

Development of Peer Instruction Material for a Cybersecurity Curriculum

Cybersecurity classes focus on building practical skills alongside the development of the open mindset that is essential to tackle the dynamic cybersecurity landscape. Unfortunately, traditional lecture-style teaching is insufficient for this task. Peer instruction is a non-traditional, active learning approach that has proven to be effective in computer science courses. The challenge in adopting peer instruction is the development of conceptual questions. This thesis presents a methodology for developing peer instruction questions for cybersecurity courses, consisting of four stages: concept identification, concept trigger, question presentation, and development. The thesis analyzes 279 questions developed over two years for three cybersecurity courses: introduction to computer security, network penetration testing, and introduction to computer forensics. Additionally, it discusses examples of peer instruction questions in terms of the methodology. Finally, it summarizes the usage of a workshop for testing a selection of peer instruction questions as well as gathering data outside of normal courses

Models of Faith: The Role of Faith-Based Organizations in International Development

Faith-based organizations make up a large percentage of organizations doing development work both domestically and internationally. Faith-based development organizations (FBDOs) can be successful because they have spiritual drive to work for the social good, and large religious organizations to support them. However, not all FBDOs practice good development, and in the past many of them have undertaken development projects that proved to be damaging and detrimental to the host communities. The purpose of this research is to explore how different FBDOs conceptualize and operationalize their faith while doing development work abroad. Through exploring different models of faith-based development and analyzing their practices, this research can ultimately assist FBDOs in structuring their organizations so they can become more effective development actors and ensure that their practices are sustainable and culturally sensitive

What Are Cybersecurity Education Papers About? A Systematic Literature Review of SIGCSE and ITiCSE Conferences

Cybersecurity is now more important than ever, and so is education in this field. However, the cybersecurity domain encompasses an extensive set of concepts, which can be taught in different ways and contexts. To understand the state of the art of cybersecurity education and related research, we examine papers from the ACM SIGCSE Technical Symposium and ACM ITiCSE conferences. From 2010 to 2019, a total of 1,748 papers were published at these conferences, and 71 of them focus on cybersecurity education. The papers discuss courses, tools, exercises, and teaching approaches. For each paper, we map the covered topics, teaching context, evaluation methods, impact, and the community of authors. We discovered that the technical topic areas are evenly covered (the most prominent being secure programming, network security, and offensive security), and human aspects, such as privacy and social engineering, are present as well. The interventions described in SIGCSE and ITiCSE papers predominantly focus on tertiary education in the USA. The subsequent evaluation mostly consists of collecting students' subjective perceptions via questionnaires. However, less than a third of the papers provide supplementary materials for other educators, and none of the authors published their dataset. Our results are relevant for instructors, researchers, and anyone new in the field of cybersecurity education, since they provide orientation in the area, a synthesis of trends, and implications for further research. The information we collected and synthesized from individual papers are organized in a publicly available dataset

Teaching how to program using automated assessment and functional glossy games (Experience Report)

Our department has long been an advocate of the functional-first school of programming and has been teaching Haskell as a first language in introductory programming course units for 20 years. Although the functional style is largely beneficial, it needs to be taught in an enthusiastic and captivating way to fight the unusually high computer science drop-out rates and appeal to a heterogeneous population of students.This paper reports our experience of restructuring, over the last 5 years, an introductory laboratory course unit that trains hands-on functional programming concepts and good software development practices. We have been using game programming to keep students motivated, and following a methodology that hinges on test-driven development and continuous bidirectional feedback. We summarise successes and missteps, and how we have learned from our experience to arrive at a model for comprehensive and interactive functional game programming assignments and a general functionally-powered automated assessment platform, that together provide a more engaging learning experience for students. In our experience, we have been able to teach increasingly more advanced functional programming concepts while improving student engagement.The authors would like to thank the precursors of the 20-year functional programming culture and FPro unit at our university, and all the instructors and TAs that have been involved in the PLab unit throughout the years. This work is financed by the ERDFs European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the Portuguese funding agency, FCT s Fundacao para a Ciencia e a Tecnologia as part of project UID/EEA/50014/2013

Spartan Daily, April 26, 2005

Volume 124, Issue 56https://scholarworks.sjsu.edu/spartandaily/10128/thumbnail.jp

To Heck With Ethics: Thinking About Public Issues With a Framework for CS Students

This paper proposes that the ethics class in the CS curriculum incorporate the Lawrence Lessig model of regulation as an analytical tool for social issues. Lessig’s use of the notion of architecture, the rules and boundaries of the sometimes artificial world within which social issues play out, is particularly resonant with computing professionals. The CS curriculum guidelines include only ethical frameworks as the tool for our students to engage with societal issues. The regulation framework shows how the market, law, social norms, and architecture can all be applied toward understanding social issues