Student mobility or academic mobility involves students moving between institutions during their post-secondary education,and one of the challenging tasks in this process is to assess the transfer credits to be offere...Student mobility or academic mobility involves students moving between institutions during their post-secondary education,and one of the challenging tasks in this process is to assess the transfer credits to be offered to the incoming student.In general,this process involves domain experts comparing the learning outcomes of the courses,to decide on offering transfer credits to the incoming students.This manual implementation is not only labor-intensive but also influenced by undue bias and administrative complexity.The proposed research article focuses on identifying a model that exploits the advancements in the field of Natural Language Processing(NLP)to effectively automate this process.Given the unique structure,domain specificity,and complexity of learning outcomes(LOs),a need for designing a tailor-made model arises.The proposed model uses a clustering-inspired methodology based on knowledge-based semantic similarity measures to assess the taxonomic similarity of LOs and a transformer-based semantic similarity model to assess the semantic similarity of the LOs.The similarity between LOs is further aggregated to form course to course similarity.Due to the lack of quality benchmark datasets,a new benchmark dataset containing seven course-to-course similarity measures is proposed.Understanding the inherent need for flexibility in the decision-making process the aggregation part of the model offers tunable parameters to accommodate different levels of leniency.While providing an efficient model to assess the similarity between courses with existing resources,this research work also steers future research attempts to apply NLP in the field of articulation in an ideal direction by highlighting the persisting research gaps.展开更多
The purpose of this article is twofold.First,it explores the order of the development of nominal and verbal gender of Amharic,which is one of the Ethio-Semitic languages.Second,it provides empirical evidence for the t...The purpose of this article is twofold.First,it explores the order of the development of nominal and verbal gender of Amharic,which is one of the Ethio-Semitic languages.Second,it provides empirical evidence for the typological plausibility of processability theory(PT).In fact,PT has been tested in typologically different languages(e.g.,English,Italian,and Japan);however,it does not have any validation from Ethiopian languages in general and Ethio-Semitic languages in particular yet.Relevant data was collected from sixteen respondents via picture description tasks,short storytelling,interviews,story re-telling,and spot the difference tasks.Distributional analysis was conducted for the analysis,and the point of emergence of target structures was determined using the emergence criteria.Accordingly,the result shows that the development of gender assignment is compatible with processability theory’s predictions in that lexical procedure precedes phrasal procedure,which is followed by S-procedure.Moreover,the masculine gender emerged earlier than its feminine counterpart at all developmental stages.However,subject agreement markers in pro-drop context emerged at stage two preceding subject verb agreement.This finding is against processability theory’s claim that suggests subject agreement markers only emerge at stage four of the processability hierarchy disregarding their stages of development in pro-drop context in particular.展开更多
文摘Student mobility or academic mobility involves students moving between institutions during their post-secondary education,and one of the challenging tasks in this process is to assess the transfer credits to be offered to the incoming student.In general,this process involves domain experts comparing the learning outcomes of the courses,to decide on offering transfer credits to the incoming students.This manual implementation is not only labor-intensive but also influenced by undue bias and administrative complexity.The proposed research article focuses on identifying a model that exploits the advancements in the field of Natural Language Processing(NLP)to effectively automate this process.Given the unique structure,domain specificity,and complexity of learning outcomes(LOs),a need for designing a tailor-made model arises.The proposed model uses a clustering-inspired methodology based on knowledge-based semantic similarity measures to assess the taxonomic similarity of LOs and a transformer-based semantic similarity model to assess the semantic similarity of the LOs.The similarity between LOs is further aggregated to form course to course similarity.Due to the lack of quality benchmark datasets,a new benchmark dataset containing seven course-to-course similarity measures is proposed.Understanding the inherent need for flexibility in the decision-making process the aggregation part of the model offers tunable parameters to accommodate different levels of leniency.While providing an efficient model to assess the similarity between courses with existing resources,this research work also steers future research attempts to apply NLP in the field of articulation in an ideal direction by highlighting the persisting research gaps.
文摘The purpose of this article is twofold.First,it explores the order of the development of nominal and verbal gender of Amharic,which is one of the Ethio-Semitic languages.Second,it provides empirical evidence for the typological plausibility of processability theory(PT).In fact,PT has been tested in typologically different languages(e.g.,English,Italian,and Japan);however,it does not have any validation from Ethiopian languages in general and Ethio-Semitic languages in particular yet.Relevant data was collected from sixteen respondents via picture description tasks,short storytelling,interviews,story re-telling,and spot the difference tasks.Distributional analysis was conducted for the analysis,and the point of emergence of target structures was determined using the emergence criteria.Accordingly,the result shows that the development of gender assignment is compatible with processability theory’s predictions in that lexical procedure precedes phrasal procedure,which is followed by S-procedure.Moreover,the masculine gender emerged earlier than its feminine counterpart at all developmental stages.However,subject agreement markers in pro-drop context emerged at stage two preceding subject verb agreement.This finding is against processability theory’s claim that suggests subject agreement markers only emerge at stage four of the processability hierarchy disregarding their stages of development in pro-drop context in particular.
