Never mind
            <i>the</i>
            paradigm, what about multiparadigm languages?

Budd, Timothy A.; Pandey, Rajeev Kumar

doi:10.1145/201998.202006

Cited by 17 publications

(5 citation statements)

References 12 publications

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“…The paradigm chosen can be very important. [59] unless one adopts "exposing students to all major paradigms through the use of a multiparadigmatic language, and does not attempt to identify" the "correct paradigm" [60].…”

Section: Choosing the Initial Programming Languagementioning

confidence: 99%

The First Programming Language and Freshman Year in Computer Science: Characterization and Tips for Better Decision Making

Sobral

2020

Advances in Intelligent Systems and Computing

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The ability to program is the "visible" competency to acquire in an introductory unit in computer science. However, before a student is able to write a program, he needs to understand the problem: before formalizing, the student must have to (be able) to think, (be able) to solve and (be able) to define. At an early stage of learning there are no significant differences between programming languages.The discussion of the early programming language continues: probably never will be a consensus among academics. The Association for Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE) computer science curriculum recommendations haven't clearly defined which programming language to adopt: it is the course directors and teachers who must make this choice, consciously and not only following the trends. This article presents a set of items that should be considered when you make a programming language choice for the first programming unit in higher education computer science courses.

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Section: Choosing the Initial Programming Languagementioning

confidence: 99%

The First Programming Language and Freshman Year in Computer Science: Characterization and Tips for Better Decision Making

Sobral

2020

Advances in Intelligent Systems and Computing

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“…To implement our breadth-first curriculum, we broke the semester into five three-week units (see Table 1) in which students would learn and practice different programming paradigms. In order to support all of these with a minimum of syntactic overhead, we heed [6] and [9] in choosing a multi-paradigm language, Python.…”

Section: Curriculummentioning

confidence: 99%

Evaluating a breadth-first cs 1 for scientists

et al. 2008

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This paper presents a thorough evaluation of CS for Scientists, a CS 1 course designed to provide future scientists with an overview of the discipline. The course takes a breadth-first approach that leverages its students' interest and experience in science, mathematics, and engineering. In contrast to many other styles of CS 1, this course does not presume that its students will study more computer science, but it does seek to prepare them should they choose to. We summarize the past year's worth of assessments of student learning, retention, and affect -with particular attention paid to women's voices. Where possible, we contrast these student measures with those from a traditional, imperative-first CS1 that this new course replaced. The data thus far suggest that CS for Scientists significantly improves students' understanding of CS, its applications, and practice.

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“…In order to support all of these with a minimum of syntactic overhead, we heed [6] and [9] in choosing a multi-paradigm language, Python. …”

Section: Curriculummentioning

confidence: 99%

Breadth-first CS 1 for scientists

Dodds

Alvarado

Kuenning

et al. 2007

Proceedings of the 12th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

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This paper describes an introductory CS course designed to provide future scientists with a one-semester overview of the discipline. The course takes a breadth-first approach that leverages its students' interest and experience in science, mathematics, and engineering. In contrast to many other styles of CS 1, this course does not presume that its students will study more computer science, but it does seek to prepare them should they choose to do so. In addition to describing the curriculum and resources, we summarize our preliminary assessments of this course and a comparison with the more traditional, imperativefirst introduction it replaced. The data thus far suggest that this CS for Scientists course improves our students' understanding of CS, its applications, and practice. KeywordsCS for scientists, introductory CS, CS 1 assessment CS FOR SCIENTISTSScrutiny seems an unavoidable fate for introductory computer science. In a field as dynamic as CS, we who teach CS0 and CS1 should strive to remain relevant and current. At the same time, we try to retain those topics and skills that enable our students to cope with next year's changes as well as last year's. This balance is particularly delicate when designing introductory CS for scientists. The evolving impact of CS on all scientific disciplines has been dramatic and well documented, e.g., [27] [29]. As George Johnson put it, "All science is computer science." [17] In contrast, many scientific programs of study present facets of CS only as needed: programming skills and styles may derive from a particular language or environment, e.g., Matlab or LabView. This approach presumably keeps such programs relevant and up-to-date, but it emphasizes particular tools over the broader computational skills so vital in all areas of science today.To leverage CS's growing importance, we replaced our traditional CS 1 course with a breadth-first version nicknamed CS for Scientists in 2006 [1]. Our goal was to create a curriculum "suitable for any student intending to major in science or engineering (including CS students)." [24] In particular, we hoped this new offering would (1) develop programming and problemsolving skills useful across engineering, mathematics, and the natural sciences, (2) attract students to continue studying CS, and (3) provide a coherent, intellectually compelling picture of computer science, even as final CS course. Context and Related WorkIt is a wonderful time to teach CS 1! Curricular innovations within introductory CS are both inspiring and numerous. Many of these experiments draw strength in a similar manner: by weaving a thematic structure amid introductory CS topics [22][15]. One of the most widespread of these themes for introductory CS is media computation [14][20]. Other themes now scaffolding CS1 include games [3][13][18][30], robotics [5], computer vision [21], and art [12][25]. In each of these cases, the thematic overlay tends to pull away from CS and toward the specifics of the course's theme. Throughout CS for Scientists we strove to kee...

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Never mind the paradigm, what about multiparadigm languages?

Cited by 17 publications

References 12 publications

The First Programming Language and Freshman Year in Computer Science: Characterization and Tips for Better Decision Making

The First Programming Language and Freshman Year in Computer Science: Characterization and Tips for Better Decision Making

Evaluating a breadth-first cs 1 for scientists

Breadth-first CS 1 for scientists

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