%0 Conference Paper %1 10.1007/978-3-031-09680-8_4 %A Rus, Vasile %A Brusilovsky, Peter %A Tamang, Lasang Jimba %A Akhuseyinoglu, Kamil %A Fleming, Scott %B Intelligent Tutoring Systems %C Cham %D 2022 %E Crossley, Scott %E Popescu, Elvira %I Springer International Publishing %K examples its2022 myown %P 36--50 %T DeepCode: An Annotated Set of Instructional Code Examples to Foster Deep Code Comprehension and Learning %X We present here a novel instructional resource, called DeepCode, to support deep code comprehension and learning in intro-to-programming courses (CS1 and CS2). DeepCode is a set of instructional code examples which we call a codeset and which was annotated by our team with comments (e.g., explaining the logical steps of the underlying problem being solved) and related instructional questions that can play the role of hints meant to help learners think about and articulate explanations of the code. While DeepCode was designed primarily to serve our larger efforts of developing an intelligent tutoring system (ITS) that fosters the monitoring, assessment, and development of code comprehension skills for students learning to program, the codeset can be used for other purposes such as assessment, problem-solving, and in various other learning activities such as studying worked-out code examples with explanations and code visualizations. We present here the underlying principles, theories, and frameworks behind our design process, the annotation guidelines, and summarize the resulting codeset of 98 annotated Java code examples which include 7,157 lines of code (including comments), 260 logical steps, 260 logical step details, 408 statement level comments, and 590 scaffolding questions. %@ 978-3-031-09680-8

@inproceedings{10.1007/978-3-031-09680-8_4, abstract = {We present here a novel instructional resource, called DeepCode, to support deep code comprehension and learning in intro-to-programming courses (CS1 and CS2). DeepCode is a set of instructional code examples which we call a codeset and which was annotated by our team with comments (e.g., explaining the logical steps of the underlying problem being solved) and related instructional questions that can play the role of hints meant to help learners think about and articulate explanations of the code. While DeepCode was designed primarily to serve our larger efforts of developing an intelligent tutoring system (ITS) that fosters the monitoring, assessment, and development of code comprehension skills for students learning to program, the codeset can be used for other purposes such as assessment, problem-solving, and in various other learning activities such as studying worked-out code examples with explanations and code visualizations. We present here the underlying principles, theories, and frameworks behind our design process, the annotation guidelines, and summarize the resulting codeset of 98 annotated Java code examples which include 7,157 lines of code (including comments), 260 logical steps, 260 logical step details, 408 statement level comments, and 590 scaffolding questions.}, added-at = {2022-06-30T21:26:31.000+0200}, address = {Cham}, author = {Rus, Vasile and Brusilovsky, Peter and Tamang, Lasang Jimba and Akhuseyinoglu, Kamil and Fleming, Scott}, biburl = {https://www.bibsonomy.org/bibtex/22cf37f68c9feb43e913c7aad19073bc8/brusilovsky}, booktitle = {Intelligent Tutoring Systems}, description = {DeepCode: An Annotated Set of Instructional Code Examples to Foster Deep Code Comprehension and Learning | SpringerLink}, editor = {Crossley, Scott and Popescu, Elvira}, interhash = {d1450816d20e3f9d64c750334c97154f}, intrahash = {2cf37f68c9feb43e913c7aad19073bc8}, isbn = {978-3-031-09680-8}, keywords = {examples its2022 myown}, pages = {36--50}, publisher = {Springer International Publishing}, timestamp = {2022-06-30T21:26:31.000+0200}, title = {DeepCode: An Annotated Set of Instructional Code Examples to Foster Deep Code Comprehension and Learning}, year = 2022 }