Modeling Programming Competency (Record no. 186941)

MARC details
000 -LEADER
fixed length control field 08555nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-47148-3
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130259.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031471483
-- 978-3-031-47148-3
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-47148-3
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number LB1028.43-1028.75
072 #7 - SUBJECT CATEGORY CODE
Subject category code JNV
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code EDU039000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code JNV
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 371.334
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kiesler, Natalie.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Modeling Programming Competency
Medium [electronic resource] :
Remainder of title A Qualitative Analysis /
Statement of responsibility, etc by Natalie Kiesler.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2024.
300 ## - PHYSICAL DESCRIPTION
Extent XVII, 165 p. 4 illus.
Other physical details online resource.
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-- computer
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-- online resource
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1 Introduction -- 1.1 Background and Motivation -- 1.2 Goal and Research Questions -- 1.3 Contextualization of this Research -- 1.4 Structure of the Book -- References -- 2 Approaching the Concept of Competency -- 2.1 Competency Definition -- 2.1.1 Psychological Perspective on Competency -- 2.1.2 Historical Perspective on Competency -- 2.1.3 Recent Perspectives and Discussions -- 22 2.2 Taxonomies and Competency Models for Computing -- 2.2.1 Bloom’s and Anderson-Krathwohl’s Taxonomy -- 2.2.2 Competency Model of the German Informatics Society -- 2.3 Competency-Based Curricula Recommendations in Computing -- 2.3.1 Information Technology 2017 -- 2.3.2 Computing Curricula 2020 -- 2.3.3 National Curricula -- Recommendations -- 2.4 Related Research in Computing Education -- References -- 3 Research Design -- 3.1 Summary of Research Desiderata -- 3.2 Research Goals -- 3.3 Research Questions -- 3.4 Study Design -- References -- Part II Data Gathering and Analysis of University Curricula -- 4 Data Gathering of University Curricula -- 4.1 Goals of Gathering and Analyzing University Curricula -- 4.2 Relevance of Gathering and Analyzing University Curricula -- 4.3 Expectations and Limitations -- 4.4 Sampling and Data Gathering -- 4.4.1 Selection of Bachelor Degree Programs -- 4.4.2 Selection of Content Area -- 4.4.3 Selection of Institutions and Study Programs -- 4.4.4 Selection of Modules -- References -- 5 Data Analysis of University Curricula -- 5.1 Methodology of the Data Analysis -- 5.2 Pre-processing of Data -- 5.2.1 Linguistic Smoothing of Competency Goals -- 5.2.2 Basic Coding Guidelines -- 5.2.3 Computer-Assisted Analysis -- 5.3 Data Analysis -- 5.3.1 Deductive Category Development -- 5.3.2 Inductive Category Development -- 5.3.3 Deductive-Inductive Category Development -- 5.4 Application of Quality Criteria -- References -- Part III Data Gathering and Analysis of Expert Interviews -- Data Gathering of Guided Expert Interviews -- 6.1 Goals of Conducting and Analyzing Guided Expert Interviews -- 6.2 Relevance of Conducting and Analyzing Guided Expert Interviews -- 6.3 Expectations and Limitations -- 6.4 Developing an Interview Guide and Questions -- 6.5 Data Gathering and Sampling -- 6.5.1 Selecting and Contacting Experts -- 6.5.2 Conducting the Interviews -- 6.5.3 Recording the Interviews -- References -- 7 Data Analysis of Guided Expert Interviews -- 7.1 Pre-processing of Data -- 7.1.1 Transcription Guidelines -- 7.1.2 Transcription System -- 7.1.3 Transcription Process -- 7.2 Data Analysis -- 7.3 Application of Quality Criteria References -- Part IV Results 8 Results of University Curricula Analysis -- 8.1 Cognitive Competencies -- 8.1.1 Cognitive Process Dimension Remembering -- 8.1.2 Cognitive Process Dimension Understanding -- 8.1.3 Cognitive Process Dimension Applying -- 8.1.4 Cognitive Process Dimension Analyzing -- 8.1.5 Cognitive Process Dimension Evaluating -- 8.1.6 Cognitive Process Dimension Creating -- 8.1.7 Knowledge Dimensions -- 8.2 Other Competencies -- 8.3 Reliability -- 8.4 Discussion of Results -- References -- 9 Results of Guided Expert Interviews -- 9.1 Cognitive Competencies -- 9.2 Other Competencies -- 9.3 Factors Preventing Programming Competency -- 9.4 Factors Contributing to Programming Competency -- 9.5 Reliability -- 9.6 Discussion of Results -- References -- 10 Summarizing and Reviewing the Components of Programming Competency -- 10.1 Summary of Cognitive Programming Competencies -- 10.2 Summary of Other Programming Competency Components -- 10.3 Review of the Anderson Krathwohl Taxonomy -- References -- Part V Wrap Up -- 11 Conclusion -- 11.1 Brief Summary of Results -- 11.1.1 Competencies Expected from Novice Programmers -- 11.1.2 Adequacy of the Anderson Krathwohl Taxonomy -- 11.1.3 Factors Influencing Students’ Competency Development -- 11.2 Conclusions -- 11.3 Future Work. References -- 12 Complete List of References.
520 ## - SUMMARY, ETC.
Summary, etc This book covers a qualitative study on the programming competencies of novice learners in higher education. To be precise, the book investigates the expected programming competencies within basic programming education at universities and the extent to which the Computer Science curricula fail to provide transparent, observable learning outcomes and assessable competencies. The study analyzes empirical data on 35 exemplary universities' curricula and interviews with experts in the field. The book covers research desiderata, research design and methodology, an in-depth data analysis, and a presentation and discussion of results in the context of programming education. Addressing programming competency in such great detail is essential due to the increasing relevance of computing in today’s society and the need for competent programmers who will help shape our future. Although programming is a core tier of computing and many related disciplines, learning how to program can be challenging in higher education, and many students fail in introductory programming. The book aims to understand what programming means, what programming competency encompasses, and what teachers expect of novice learners. In addition, it illustrates the cognitive complexity of programming as an advanced competency, including knowledge, skills, and dispositions in context. So, the purpose is to communicate the breadth and depth of programming competency to educators and learners of programming, including institutions, curriculum designers, and accreditation bodies. Moreover, the book’s goal is to represent how a qualitative research methodology can be applied in the context of computing education research, as the qualitative research paradigm is still an exception in computing education research. The book provides new insights into programming competency. It outlines the components of programming competencies in terms of knowledge, skills, and dispositions and their cognitive complexity according to the CC2020 computing curricula and the Anderson-Krathwohl taxonomy of the cognitive domain. These insights are essential as programming constitutes one of the most relevant competencies in all computing study programs. In addition, being able to program describes the capability of solving problems, which is also a core competency in today’s increasingly digitalized society. In particular, the book reveals the great relevance of dispositions and other competency components in programming education, which curricula currently fail to recognize and specify. In addition, the book outlines the resulting implications for higher education institutions, educators, and student expectations. Yet another result of interest to graduate students is the multi-method study design that allows for the triangulation of data and results.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Education
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Educational technology.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer programming.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computers and Education.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Digital Education and Educational Technology.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Programming Techniques.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031471476
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031471490
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031471506
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-47148-3">https://doi.org/10.1007/978-3-031-47148-3</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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