Mob Programming: The State of the Art and Three Case Studies of Open Source Software

Kattan, Herez Moise; Oliveira, Frederico; Goldman, Alfredo; Yoder, Joseph W.

doi:10.1007/978-3-319-73673-0_12

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…Mob Programming is an approach used in software development where a team simultaneously work on the same output, at the same time, in the same environment. The benefits of this approach range from facilitated knowledge sharing and learning to the use of distributed knowledge [27]. During Mob Programming team members swap roles to facilitate learning, disseminate knowledge and to make sure no single person dominates the output.…”

Section: Analytics For Informal Learningmentioning

confidence: 99%

Professional Learning Analytics

Littlejohn¹

2022

The Handbook of Learning Analytics

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Professional learning is an important component of productivity in contemporary work environments characterised by continual change. Learning for work takes various forms, from formal training to informal learning through work activities. In many work settings professionals collaborate via networked environments leaving various forms of digital traces and ‘clickstream’ data. These data can be exploited through learning analytics to make both formal and informal learning processes traceable and visible to support professionals with their learning. This chapter examines the state-of-the-art in professional learning analytics by considering the different ways professionals learn. As learning analytics techniques advance, the modelling techniques that underpin these methods become increasingly complex and the assumptions that underpin the analytics become ever-more embedded within the system. This chapter questions these assumptions and calls for a new, refreshed vision of professional learning analytics for the future which is based on how professionals learn. There is a need to broaden our thinking about the purpose of learning analytics build systems that effectively to address affective and motivational learning issues as well as technical and practical expertise; intelligently align individual learning activities with organisational learning goals and to be wary of attempts to embed professional expertise in code written by software developers, rather than by the professionals themselves. There are also ethical concerns about the degree of surveillance on learners as they work and learn with anxieties about whether people understand the (potentially serious) consequences. Finally, learning analytics generally are developed for formal learning contexts, in schools, colleges and universities, missing opportunities to provide the support professionals need as they learn through everyday work.

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Section: Analytics For Informal Learningmentioning

confidence: 99%

Professional Learning Analytics

Littlejohn¹

2022

The Handbook of Learning Analytics

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“…Mob programming sessions aim to complete specific programming improvement assignments while working together with the client [7]. Advantages include an organized cycle for utilizing distributed information and a greater code fulfillment due to the inherent sharing of information and experience among the participants [8].…”

Section: Introductionmentioning

confidence: 99%

Comparing Participants’ Brainwaves During Solo, Pair, and Mob Programming

Shiraishi

Washizaki

Saito

et al. 2021

Lecture Notes in Business Information Processing

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Participants’ feelings and impressions utilizing electroencephalography (EEG) and the effectiveness of code are compared for different types of programming sessions. EEG information is obtained as an alternate viewpoint during three programming sessions (solo, pair, and mob programming). MindWave Mobile 2 (brainwave detector) is equipped to collect the attention levels, meditation levels, and EEG brainwaves. These data are utilized to distinguish efficiencies, weaknesses, and points of interest by programming session. The results provide preliminary information to distinguish between the three sessions, but further studies are necessary to make firm conclusions. Additionally, alternative methods or systems are required to analyze the collected data.

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