@techreport{TR-IC-19-05,
   number = {IC-19-05},
   author  =  {Ricardo  Caceffo and Pablo Frank-Bolton and Renan Souza
                   and Rodolfo Azevedo},
   title   =   {Identifying   and  Validating  Java  Misconceptions  – 
                   Complementary Material},
   month = {April},
   year = {2019},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 48 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       This  Technical  Report presents complementary material related
       to  the article “Identifying and Validating Java Misconceptions
       Toward  a  CS1  Concept  Inventory”,  to  be  published  in the
       Proceedings of the 24th Annual ACM Conference on Innovation and
       Technology  in  Computer  Science  Education  (ITiCSE 2019). \\
       \textbf{Article   Abstract:}   A   misconception  is  a  common 
       misunderstanding that students may have about a specific topic.
       The    identification,   documentation,   and   validation   of  
       misconceptions  is  a  long  and  time-consuming  work, usually
       carried  out  using  iterative  cycles  of  students  answering 
       open-ended  questionnaires,  interviews  with  instructors  and 
       students,   exam  analysis,  and  discussion  with  experts.  A 
       comprehensive  list of validated misconceptions in some subject
       can be used to build formal evaluation methods like the Concept
       Inventory (CI), a multiple-choice questionnaire that is usually
       performed  as  pre-post  tests in order to assess any change in
       student  understanding.  In  CS1, validated misconceptions were
       identified   and   documented   in  C  and  Python  programming 
       languages. Although there are studies related to misconceptions
       in  the Java language, these misconceptions lack the formality,
       comprehensiveness,   and  robustness  of  their  C  and  Python 
       counterparts.  On  this work, we propose a methodology to adapt
       the   validated   misconceptions  in  C  and  Python  to  Java. 
       Initially,  through  the  analysis  of  an  initial  list of 33
       misconceptions  in  C  and  28  in  Python,  we  identified and
       documented  in an antipattern format 31 possible misconceptions
       in  Java.  We  then  developed a final term exam, composed of 7
       open-ended  questions,  in  which each question was designed to
       address  some  of the misconceptions covered in the course (N =
       27).  Through  the  analysis  of  the  exam’s  answers  (N = 69
       students), it was possible to validate 22 of the misconceptions
       (81\%).  Also, 6 new misconceptions were identified, leading to
       a total of 28 valid misconceptions in Java.
  }
}