From Critique to Computational Thinking: A Peer-Assessment-Supported Problem Identification, Flow Definition, Coding, and Testing Approach for Computer Programming Instruction

Scholars believe that computational thinking is one of the essential competencies of the 21st century and computer programming courses have been recognized as a potential means of fostering students’ computational thinking. In tradition instruction, PFCT (problem identification, flow definition, coding, and testing) is a commonly adopted procedure to guide students to learn and practice computer programming. However, without further guidance, students might focus on learning the syntax of computer programming language rather than the concept of solving problems. This study proposes a peer-assessment-supported PFCT (PA-PFCT) approach for boosting students’ computer programming knowledge and computational thinking awareness. A quasi-experiment was conducted on a computer programming course in a high school to evaluate its influence on students’ learning achievement, computational thinking awareness, learning motivation, and self-efficacy. An experimental group of 51 students learned with the proposed approach, while a control group of 49 students learned with the traditional PFCT (T-PFCT) approach. The experimental results show that the proposed approach significantly enhanced the students’ computational thinking awareness, learning motivation, and self-efficacy, while not having significant impacts on their computer programming knowledge test scores.

Analyzing novices' fun and programming behaviours while playing a serious blocks-based game

Blocks-based environments have been used to promote programming learning mostly in elementary and middle schools. In many countries, isolated initiatives have been launched to promote programming learning among children, but until now there is no evidence of widespread use of this type of environment in Brazil and Portugal. Consequently, it is common that many students reach higher education with little or no programming knowledge and skills. NoBug’s SnackBar is a game designed to help promote programming learning. This study examined students' behavior and attitudes when playing the game on their initiative. It used a sample of 33 undergraduate students enrolled in an introductory programming course. The variables studied were students' performance and engagement, satisfaction, and problem-solving strategies. The main findings were (1) better performing students had a high level of perceived learning, (2) all the students had similar perceptions about their fun while playing, (3) the leader board was the most used game element not directly related to learning and (4) the top-ranked students access previous solutions to help them solve a new mission, while the others often use a trial-and-error approach.

Processing binding data using an open-source workflow

The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (FBLD) to detect protein–ligand interactions. By comparing the thermal stability of a target protein in the presence and absence of a ligand, potential binders can be identified. The technique is easy to set up, has low protein consumption, and can be run on most real-time polymerase chain reaction (PCR) instruments. While data analysis is straightforward in principle, it becomes cumbersome and time-consuming when the screens involve multiple 96- or 384-well plates. There are several approaches that aim to streamline this process, but most involve proprietary software, programming knowledge, or are designed for specific instrument output files. We therefore developed an analysis workflow implemented in the Konstanz Information Miner (KNIME), a free and open-source data analytics platform, which greatly streamlined our data processing timeline for 384-well plates. The implementation is code-free and freely available to the community for improvement and customization to accommodate a wide range of instrument input files and workflows. Graphical Abstract

POTATO: An automated pipeline for batch analysis of optical tweezers data

Optical tweezers is a single-molecule technique that allows probing of intra- and intermolecular interactions that govern complex biological processes involving molecular motors, protein-nucleic acid interactions and protein/RNA folding. Recent developments in instrumentation eased and accelerated optical tweezers data acquisition, but analysis of the data remains challenging. Here, to enable high-throughput data analysis, we developed an automated python-based analysis pipeline called POTATO (Practical Optical Tweezers Analysis TOol). POTATO automatically processes the high-frequency raw data generated by force-ramp experiments and identifies (un)folding events using predefined parameters. After segmentation of the force-distance trajectories at the identified (un)folding events, sections of the curve can be fitted independently to worm-like chain and freely-jointed chain models, and the work applied on the molecule can be calculated by numerical integration. Furthermore, the tool allows plotting of constant force data and fitting of the Gaussian distance distribution over time. All these features are wrapped in a user-friendly graphical interface (https://github.com/REMI-HIRI/POTATO), which allows researchers without programming knowledge to perform sophisticated data analysis.

Auto-qPCR; a python-based web app for automated and reproducible analysis of qPCR data

Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app (https://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

Effects of LEGO robotic on freshmen students' computational thinking and programming learning attitudes in Taiwan

PurposeAdvancements in technology require that everyone is skilled with computational thinking (CT), problem-solving and computer programming skills. This study aims to examine the development of CT in problem-solving skills (PSS) and programming learning attitude by integrating LEGO robotics kits in a project-based learning course.Design/methodology/approachThis study examines the development of CT in PSS and programming learning attitude by integrating LEGO robotics kits in a project-based learning course. This study consists of a single group pre-post-test research design with 32 freshmen university students. Quantitative and qualitative data were collected by pre-post-tests and recording of classroom discussions, respectively.FindingsTherefore, this finding implies that robotics can be used to develop CT in university students; however, there is a need for designing curricula with advanced robotic kits as artificial intelligence (AI) has become more prevalent. Hence, programming knowledge learned will help students to understand the application of robots in AI.Originality/valueThe study creates educators' awareness that CT skills might be developed in freshmen university students through robotics. However, many still consider them toys rather than learning aids.

Educators as Gamemasters

Although multiple studies have shown the efficacy of Serious Games (SGs) in improving students' performance and learning experience, the wide use of SGs is yet to be realised. One of the challenges towards the adoption of SGs can be attributed to the complex and costly development process. In this paper, we present ARQS (Authentic Role-playing-game Quest System) tool, an educator-oriented authoring tool we developed for supporting the implementation of a serious role-playing-game (RPG). The authoring tool consists of features that simplify the creation of important RPG components e.g. avatars, virtual world. Furthermore, the authoring process employs block-based programming to configure aspects of RPG such as creating quests. The concept is adopted in order to provide a platform where educators without programming knowledge are able to use. A formative evaluation was conducted with ten educators from secondary and university levels, using a low-fidelity prototype. Outcomes from the evaluation showed promising results, attesting the potential of ARQS as an educational tool for the creation of interactive learning instructions in the form of real-world scenarios embedded within a role-playing-game.

Enterprise Robotic Process Automation

Robotic Process Automation (RPA) is an emerging technology widely used across multiple sectors such as human resources, healthcare, finance, accounting, manufacturing, higher education and supply chain management, etc. RPA, also known as ‘software bots’, replaces manual, rule-based, repetitive tasks humans perform. These software bots are currently in a journey, evolving to be more sophisticated, mimicking human activities and enabling humans to achieve higher-valued tasks. Hence, RPA impacts the overall operational efficiency in organisations through multiple facets by its integration with employees, existing technologies and infrastructure, and business processes. It reduces the burden on IT as it does not disturb the underlying legacy systems. It increases reliability as bots can work 24x7 effectively. It is used as a time and cost reduction technology as it reduces the size of the manual workload. The tasks performed through RPA is accurate as it is less prone to errors. It increases compliances as it follows the rules and keeps audit trails. The productivity rate of organisations increase as the execution time through RPA is faster than tasks being performed by human employees. Furthermore, RPA is introduced as a low code technology that uses drag and drop functionalities with little to no programming knowledge [1].

Aligning and Assessing Teaching Approaches With SOLO Taxonomy in a Computer Programming Course

A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement) approach in the IP course which focuses on both programming knowledge (syntax and semantics) and problem solving strategies. We compared the teaching and learning approach of the IP course with the five levels of SOLO taxonomy. We assessed the students’ performance by using different assessment tasks based on the four stages of the ADRI approach. Results show that the current teaching and learning approach of the IP course addressed all the five levels of SOLO taxonomy. The students’ performance in the Approach and Result stages (82%) are good, and the performance in the Improvement (71%) and Deployment (69%) stages are satisfactory. Overall, the ADRI approach provides positive impact on the teaching and learning process of the IP course.

Aligning and Assessing Teaching Approaches With SOLO Taxonomy in a Computer Programming Course

A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement) approach in the IP course which focuses on both programming knowledge (syntax and semantics) and problem solving strategies. We compared the teaching and learning approach of the IP course with the five levels of SOLO taxonomy. We assessed the students’ performance by using different assessment tasks based on the four stages of the ADRI approach. Results show that the current teaching and learning approach of the IP course addressed all the five levels of SOLO taxonomy. The students’ performance in the Approach and Result stages (82%) are good, and the performance in the Improvement (71%) and Deployment (69%) stages are satisfactory. Overall, the ADRI approach provides positive impact on the teaching and learning process of the IP course.