Prompt Problems: A New Programming Exercise for the Generative AI Era

Large Language Models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused on code writing tasks, but there is now a shift in importance towards code reading, comprehension and evaluation of LLM-generated code. Alongside this shift, an important new skill is emerging -- the ability to solve programming tasks by constructing good prompts for code-generating models. In this work we introduce a new type of programming exercise to hone this nascent skill: 'Prompt Problems'. Prompt Problems are designed to help students learn how to write effective prompts for AI code generators. A student solves a Prompt Problem by crafting a natural language prompt which, when provided as input to an LLM, outputs code that successfully solves a specified programming task. We also present a new web-based tool called Promptly which hosts a repository of Prompt Problems and supports the automated evaluation of prompt-generated code. We deploy Promptly for the first time in one CS1 and one CS2 course and describe our experiences, which include student perceptions of this new type of activity and their interactions with the tool. We find that students are enthusiastic about Prompt Problems, and appreciate how the problems engage their computational thinking skills and expose them to new programming constructs. We discuss ideas for the future development of new variations of Prompt Problems, and the need to carefully study their integration into classroom practice.Comment: Accepted to SIGCSE'24. arXiv admin note: substantial text overlap with arXiv:2307.1636

A systematic review of the effect of therapeutic drug monitoring on patient health outcomes during treatment with penicillins.

Background Dosing regimens guided by therapeutic drug monitoring (TDM) may be able to improve penicillin exposure in patients, which could result in improved patient health outcomes. Objectives This systematic review aims to describe the impact penicillin TDM has on health outcomes, including antimicrobial resistance (AMR). Methods Studies measuring penicillins in patient samples that adjusted regimens according to the result, and reported health outcomes were selected. Study bias was assessed according to study type. Included study characteristics were tabulated and described by narrative synthesis. Results Three randomized controlled trials (RCTs), 16 cohort studies, and 9 case studies were included. No RCTs showed statistically significant improvements in health outcomes. Five cohort studies showed improvement in at least one health outcome associated with target attainment. However, there was a high risk of bias in all studies for health outcomes. One study assessed the impact of penicillin TDM on AMR and found that improved target attainment was associated with suppression of resistance. No studies found a detrimental effect of penicillin TDM. Conclusions There is little evidence to suggest that TDM improves health outcomes, however neither health outcomes nor impact on AMR were adequately addressed. Variations in TDM implementation meant that a meta-analysis was not suitable. Penicillin TDM needs standardization, however there is currently no clear evidence of optimal conditions. Suitably powered studies are required to resolve the ambiguity surrounding the impact of TDM on clinical outcomes, including AMR. Further, standardized protocols and concentration targets need to be identified for TDM to be implemented successfully

A Systematic Review of the Effect of Therapeutic Drug Monitoring on Patient Health Outcomes during Treatment with Carbapenems

Adjusting dosing regimens based on measurements of carbapenem levels may improve carbapenem exposure in patients. This systematic review aims to describe the effect carbapenem therapeutic drug monitoring (TDM) has on health outcomes, including the emergence of antimicrobial resistance (AMR). Four databases were searched for studies that reported health outcomes following adjustment to dosing regimens, according to measurements of carbapenem concentration. Bias in the studies was assessed with risk of bias analysis tools. Study characteristics and outcomes were tabulated and a narrative synthesis was performed. In total, 2 randomised controlled trials (RCTs), 17 non-randomised studies, and 19 clinical case studies were included. Significant variation in TDM practice was seen; consequently, a meta-analysis was unsuitable. Few studies assessed impacts on AMR. No significant improvement on health outcomes and no detrimental effects of carbapenem TDM were observed. Five cohort studies showed significant associations between achieving target concentrations and clinical success, including suppression of resistance. Studies in this review showed no obvious improvement in clinical outcomes when TDM is implemented. Optimisation and standardisation of carbapenem TDM practice are needed to improve intervention success and enable study synthesis. Further suitably powered studies of standardised TDM are required to assess the impact of TMD on clinical outcomes and AMR

"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers

Recent developments in deep learning have resulted in code-generation models that produce source code from natural language and code-based prompts with high accuracy. This is likely to have profound effects in the classroom, where novices learning to code can now use free tools to automatically suggest solutions to programming exercises and assignments. However, little is currently known about how novices interact with these tools in practice. We present the first study that observes students at the introductory level using one such code auto-generating tool, Github Copilot, on a typical introductory programming (CS1) assignment. Through observations and interviews we explore student perceptions of the benefits and pitfalls of this technology for learning, present new observed interaction patterns, and discuss cognitive and metacognitive difficulties faced by students. We consider design implications of these findings, specifically in terms of how tools like Copilot can better support and scaffold the novice programming experience.Comment: 26 pages, 2 figures, TOCH

Passive impedance sensing using a SAW resonator-coupled biosensor for zero-power wearable applications

A bio-sensing scheme, which acquires impedance information of a capacitive biosensor by using the reflected RF signal from a surface acoustic wave (SAW) resonator connected to the biosensor, is proposed. This technique requires no power to be supplied to the biosensor node and hence is highly applicable to wearable applications. Theoretical analysis has demonstrated that the sensitivity of the SAW resonator-coupled biosensor is higher than that of traditional impedance loaded SAW sensors and therefore it is more suitable for measuring the very small impedance changes in biosensors. The passive detection of the change in the impedance of a capacitive biosensor, as a result of biological binding events associated with the capture of a target analyte, has been demonstrated by preliminary experimentation. Dry tests of the SAW coupled capacitive biosensor using a cable connected network analyzer showed the aF level capacitance measurement resolution, which was only achieved in transistor level circuits previously, could be attained. When liquid samples with concentrations of C-Reactive Protein (CRP) in the range of 0.1 to 2 μg/ml were applied to the biosensor, a corresponding change in the resonant frequency of the SAW resonator-coupled biosensor (in the order of sub-hundred kHz) was observed. This has demonstrated the potential for applying this technique in applications where a zero-power requirement at the biosensor node could be a distinct advantage, when the cable link between the network analyzer and the biosensor node is replaced by the RF transmission

Mr. Meteo: Providing climate information for the unconnected

A majority of the world remain unconnected to the World Wide Web due to issues like low literacy and relevant information. This study presents Mr. Meteo, a system that provides weather information via voice calls in local languages to rural farmers in Ghana. The study used an interdisciplinary approach to identify relevant informational needs and socio-economic implications, and early end-user and stakeholder involvement. Mr. Meteo was deployed in Bolgatanga, Ghana and represents a novel design in terms of actual web data access to rural areas. The positive feedback from farmers, and stakeholder’s interest in continuity, shows this approach to be an appropriate method of development and implementation of information systems for rural areas; successful due to end-user and stakeholder involvement, focus on existing technologies, the use of voice technologies to mitigate the problem of illiteracy, and information relevance to end-users. This paper presents the methodology and results of this novel, practical, local-context ICT4D project,that has produced a viable information system for rural communities

How to improve the peer review method: Free-selection vs assigned-pair protocol evaluated in a computer networking course

This study provides field research evidence on the efficiency of a “free-selection” peer review assignment protocol as compared to the typically implemented “assigned-pair” protocol. The study employed 54 sophomore students who were randomly assigned into three groups: Assigned-Pair (AP) (the teacher assigns student works for review to student pairs), Free-Selection (FS) (students are allowed to freely explore and select peer work for review), and No Review (NR) (control group). AP and FS student groups studied and reviewed peer work in the domain of Computer Networking, supported by a web-based environment designed to facilitate the two peer review protocols. Our results indicate that students following the Free Selection protocol demonstrate (a) better domain learning outcomes, and (b) better reviewer skills, compared to the AP condition. Overall, the study analyzes the benefits and shortcomings of the FS vs AP review assignment protocol, providing evidence that the FS condition can be multiply beneficial to students who engage in peer review activities

Kaposi's Sarcoma-Associated Herpesvirus ORF45 Interacts with Kinesin-2 Transporting Viral Capsid-Tegument Complexes along Microtubules

Open reading frame (ORF) 45 of Kaposi's sarcoma-associated herpesvirus (KSHV) is a tegument protein. A genetic analysis with a null mutant suggested a possible role for this protein in the events leading to viral egress. In this study, ORF45 was found to interact with KIF3A, a kinesin-2 motor protein that transports cargoes along microtubules to cell periphery in a yeast two-hybrid screen. The association was confirmed by both co-immunoprecipitation and immunoflorescence approaches in primary effusion lymphoma cells following virus reactivation. ORF45 principally mediated the docking of entire viral capsid-tegument complexes onto the cargo-binding domain of KIF3A. Microtubules served as the major highways for transportation of these complexes as evidenced by drastically reduced viral titers upon treatment of cells with a microtubule depolymerizer, nocodazole. Confocal microscopic images further revealed close association of viral particles with microtubules. Inhibition of KIF3A–ORF45 interaction either by the use of a headless dominant negative (DN) mutant of KIF3A or through shRNA-mediated silencing of endogenous KIF3A expression noticeably decreased KSHV egress reflecting as appreciable reductions in the release of extracellular virions. Both these approaches, however, failed to impact HSV-1 egress, demonstrating the specificity of KIF3A in KSHV transportation. This study thus reports on transportation of KSHV viral complexes on microtubules by KIF3A, a kinesin motor thus far not implicated in virus transportation. All these findings shed light on the understudied but significant events in the KSHV life cycle, delineating a crucial role of a KSHV tegument protein in cellular transport of viral particles

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01