Inhalt

Abstract:

Tech Writing B2: Computer Science/IT is a course developed specifically for students from computer science and IT backgrounds who wish to hone their technical English writing skills.

Gliederung:

Skills to learn were derived from real-world applications specific to computer scientists for the purpose of improving explanations, sentence and written structure, logic in writing, maintaining objectivity and precision, using online tools for the writing process and data analysis. Further, a brief review of hypotheticals and the appropriateness of active versus passive voice in technical writing is covered.
These topics are covered over the course of four separate modules. The first addresses deepfake technology, which exemplified legitimate versus illegitimate sources. Here, students are introduced to hypotheticals as a review. Next, particularly problematic punctuation in English – commas, semicolons and hyphens – are reviewed. Finally, the module concludes with a guided tour of online writing resources to ease the writing process.
In module 2, students will learn how to write software documentation as well as the appropriate phraseology for this text type. This is accompanied by how students can best draft and revise their written work. Identifying and extracting collocations for students personal expansion of their vocabulary is another core skill of module 2. Finally, typical pitfalls in academic and technical writing are introduced so that students can more closely adhere to conventions of computer science texts.
The third module covers data mediation, which involves describing, analyzing and interpreting data in line graphs, bar charts and pie charts. Relevant vocabulary and phraseology are presented and practiced at length there. Further, describing how code works by using pseudocode is a core skill this module covers. Typical structures students can employ and relevant vocabulary for these structures are taught. Finally, sign-posting devices are introduced as a way to ensure structural and logical development in students‘ writing.
The fourth and final module primarily covers paraphrasing, summarizing and sentence reformulation. Being able to rewrite what others have written but in your own words is a skill required both in research and in professional contexts. It is additionally important for ensuring that others‘ work is not plagiarized. This skill is complemented by learning how to diversify sentence structure through sign-posting devices and advanced language expressions.

Detaillierter Inhalt:

Module 1: Writing Mechanics and Online Writing Tools
· Chapter 1: Deepfake Technology
· Chapter 2: Hypotheticals
· Chapter 3: Comma, semicolon and hyphen rules
· Chapter 4: Online writing research & reference tools

Module 2: Software Documentation & The Revising Process
· Chapter 1: Software Documentation
· Chapter 2: Extracting Collocations
· Chapter 3: Drafting and Revising
· Chapter 4: Things to Avoid in Academic Writing
· Chapter 5: Active and Passive Voice

Module 3: Describing Data Analytics and Code
· Chapter 1: Digital Twin Technologies
· Chapter 2: Describing Code to Others through Pseudocode
· Chapter 3: Data Analysis and Expression in Trend Figures
· Chapter 4: Sign-Posting as a Scaffolding Tool

Module 4: Paraphrasing and Sentence Diversification
· Chapter 1: Closed vs Open-Source Software
· Chapter 2: Paraphrasing Techniques
· Chapter 3: Summary Writing
· Chapter 4: Diversifying Sentence Structure

Lern-/Qualifikationsziele:

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Lehrveranstaltungstyp:

Kurs

Interaktionsformen mit Betreuer/in:

E-Mail

Interaktionsformen mit Mitlernenden:

E-Mail

Kursdemo:

zur Kursdemo

Nutzung

Kurs ist konzipiert für:

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Formale Voraussetzungen:

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Erforderliche Vorkenntnisse:

Students should have already completed an English course at the B1 level or be tested into the B2 level through their university‘s placement test. Since the course is directed at computer scientists, a working knowledge of concepts from the computer science field will be beneficial. All materials used for the course stem from authentic computer science contexts. Not having the relevant computer science skills or knowledge is not required but it will make some of the content more difficult to understand.

Hinweise zur Nutzung:

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Kursumsetzung (verwendete Medien):

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Erforderliche Technik:

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Nutzungsentgelte:

für andere Personen als (reguläre) Studenten der vhb Trägerhochschulen nach Maßgabe der Benutzungs- und Entgeltordnung der vhb

Rechte hinsichtlich des Kursmaterials:

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Verantwortlich

Anbieterhochschule:

Uni Erlangen-Nürnberg (FAU)

Anbieter:

Dr. G. Lorenz

Paul Hobbs-Koch

Autoren:

Paul Hobbs-Koch

Paul Gahman

Betreuer:

Paul Hobbs-Koch

Prüfung

Portfolio-Prüfung

Art der Prüfung:

Übungsaufgaben

Bemerkung:

Die Prüfung besteht aus mehreren Modulquizzes sowie Portfolioabgaben

Prüfer:

Dr. Gunter Lorenz

Prüfungsanmeldung erforderlich:

ja

Anmeldeverfahren:

Weitere Informationen werden den Teilnehmer:innen direkt mitgeteilt.

Prüfungsanmeldefrist:

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Prüfungsabmeldefrist:

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Kapazität:

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Prüfungsdatum:

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Prüfungszeitraum:

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Prüfungsdauer:

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Prüfungsort:

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Zuständiges Prüfungsamt:

Prüfungsamt der Heimathochschule

Zugelassene Hilfsmittel:

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Formale Voraussetzungen für die Prüfungsteilnahme:

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Inhaltliche Voraussetzungen für die Prüfungsteilnahme:

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Zertifikat:

Ja (benoteter Schein)

Anerkennung:

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