Framing student evaluations of university learning and teaching : discursive strategies and textual outcomes

Evaluation in higher education is an evolving social practice, that is, it involves what people, institutions and broader systems do and say, how they do and say it, what they value, the effects of these practices and values, and how meanings are ascribed. The textual products (verbal, written, visual, gestural) that inform and are produced by, for and through evaluative practices are important as they promulgate particular kinds of meanings and values in specific contexts. This paper reports on an exploratory study that sought to investigate, using discourse analysis, the types of evaluative practices that were ascribed value, and the student responses that ensued, in different evaluative instruments. Findings indicate that when a reflective approach is taken to evaluation, students’ responses are more considered, they interrogate their own engagement in the learning context and they are more likely to demonstrate reconstructive thought. These findings have implications for reframing evaluation as reflective learning.

Using textual analysis with Concept Inventories to identify root causes of misconceptions

Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Methods for Answer Extraction in Textual Question Answering

In this thesis we present and evaluate two pattern matching based methods for answer extraction in textual question answering systems. A textual question answering system is a system that seeks answers to natural language questions from unstructured text. Textual question answering systems are an important research problem because as the amount of natural language text in digital format grows all the time, the need for novel methods for pinpointing important knowledge from the vast textual databases becomes more and more urgent. We concentrate on developing methods for the automatic creation of answer extraction patterns. A new type of extraction pattern is developed also. The pattern matching based approach chosen is interesting because of its language and application independence. The answer extraction methods are developed in the framework of our own question answering system. Publicly available datasets in English are used as training and evaluation data for the methods. The techniques developed are based on the well known methods of sequence alignment and hierarchical clustering. The similarity metric used is based on edit distance. The main conclusions of the research are that answer extraction patterns consisting of the most important words of the question and of the following information extracted from the answer context: plain words, part-of-speech tags, punctuation marks and capitalization patterns, can be used in the answer extraction module of a question answering system. This type of patterns and the two new methods for generating answer extraction patterns provide average results when compared to those produced by other systems using the same dataset. However, most answer extraction methods in the question answering systems tested with the same dataset are both hand crafted and based on a system-specific and fine-grained question classification. The the new methods developed in this thesis require no manual creation of answer extraction patterns. As a source of knowledge, they require a dataset of sample questions and answers, as well as a set of text documents that contain answers to most of the questions. The question classification used in the training data is a standard one and provided already in the publicly available data.

Insights into students' conceptual understanding using textual analysis: A case study in signal processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

Using Relationships for Matching Textual Domain Models with Existing Code

We address the task of mapping a given textual domain model (e.g., an industry-standard reference model) for a given domain (e.g., ERP), with the source code of an independently developed application in the same domain. This has applications in improving the understandability of an existing application, migrating it to a more flexible architecture, or integrating it with other related applications. We use the vector-space model to abstractly represent domain model elements as well as source-code artifacts. The key novelty in our approach is to leverage the relationships between source-code artifacts in a principled way to improve the mapping process. We describe experiments wherein we apply our approach to the task of matching two real, open-source applications to corresponding industry-standard domain models. We demonstrate the overall usefulness of our approach, as well as the role of our propagation techniques in improving the precision and recall of the mapping task.

Efecto de secuencia de cultivos y métodos de control de malezas sobre la dinámica de las malezas y el rendimiento del frijol común (Phaseolus vulgaris L.) postrera, 1997

El presente estudio se llevó a cabo en la Finca Experimental La Compañía, en el municipio de San Marcos– Carazo, Nicaragua, durante la postrera de 1997. Los objetivos fueron determinar el efecto de rotación de cultivos y métodos de control de malezas sobre la abundancia, biomasa y cobertura de las malezas en el cultivo del frijol común, así como el efecto sobre el rendimiento del cultivo y el beneficio económico que de él se deriva. Se estableció un experimento bifactorial en diseño de parcelas divididas, con cuatro repeticiones. El factor A secuencia de cultivo como parcela principal incluye los cultivos a 1), maíz, a2), sorgo, a3), frijol y a4) maleza y el factor B controles de maleza en las sub parcelas incluye: b1) control cultural, (cobertura muerta), b2) control mecánico, (uso de machete) y b3) control químico (herbicidas post-emergentes Flauzifop-butil y fomesafen). El análisis de las variables muestra efecto de los factores en estudio y muy pocas interacciones, por tanto a lo largo del documento se reportan y discuten los resultados de los factores por separado (efectos principales). En el estudio se lograron identificar 27 especies de maleza, de las cuales 16 pertenecen a la clase dicotiledónea y 11 a la clase monocotiledónea. Los mejores rendimientos se obtuvieron con la rotación maleza–frijol. Los mejores beneficios netos se presentaron en la rotación maleza–frijol. Respecto a los controles de maleza, el control químico ejerció mejor control sobre las malezas, contrario al control mecánico y el control cultural.

Comportamiento de las malezas y el rendimiento de frijol común (Phaseolus vulgaris L.) bajo sistemas de labranza y secuencia de cultivos, resultados de tres años de estudio, (1994, 1995 y 1996)

La producción de frijol común (Phaseolus vulgaris L.), carece de información referente al efecto combinado de sistemas de labranza y secuencia de cultivos sobre el comportamiento de las malezas y el rendimiento. Este estudio se condujo con el propósito de determinar el comportamiento de tres sistemas de labranza (cero, mínima y convencional) en combinación con secuencia de cultivos (frijol-frijol y maíz-frijol), sobre la dinámica de las malezas y el rendimiento de frijol común. La investigación se llevó a cabo durante los años 1994, 1995 y 1996 en la finca experimental La Compañía, municipio de San Marcos, departamento de Carazo. Los suelos de la estación experimental son franco arenoso y han sido sembrados con frijol en secuencia durante los últimos seis años. El diseño experimental que se utilizó en el estudio fue de parcelas divididas, arregladas en bloques completos al azar (BCA) con cuatro repeticiones. El sistema de labranza mínima presentó mejor comportamiento en las variables del rendimiento: número de plantas por metro cuadrado (29.5), vainas por planta (7.83), peso de cien granos (18.79 g) y rendimiento de grano (1542.5 kg ha-1 , no así en labranza cero y convencional. El sistema de labranza Mínima permite mejorar la eficiencia del rendimiento de dicho cultivo y presenta mayores ventajas económicas Los resultados obtenidos en la secuencia de cultivos no muestran una clara tendencia afectando el rendimiento de grano de frijol.

Secuencia de cultivos y control de malezas en frijol común (Phaseolus vulgaris L.) efecto sobre la dinámica de malezas y el rendimiento del cultivo en el período de 1994-1996

En el presente trabajo se recopiló y analizó información proveniente de trabajos realizados durante los años 1994, 1995 y 1996, con el propósito de analizar el comportamiento de la secuencia de cultivos y controles de malezas sobre el crecimiento y rendimiento del cultivo del fríjol común, así como el comportamiento de las malezas en el tiempo. Los ensayos se establecieron en la estación experimental La Compañía ubicada en el municipio de San Marcos, Carazo. En el campo se utilizó un diseño de parcelas divididas en arreglos de bloques completos al azar con cuatro repeticiones, estableciéndose en la parcela grande las secuencias de cultivos (secuencia maíz-fríjol y fríjol-fríjol) y en la sub-parcela los controles de malezas (control cultural, mecánico y químico). Para conocer el efecto del tiempo sobre los factores en estudio, en el modelo estadístico utilizado para el análisis, se incluyó el factor tiempo. Los datos recopilados de las variables en estudio fueron sometidos a análisis de varianza. En casos donde se encontraron diferencias significativas, las medias se separaron a través de procedimientos de diferencia mínima significativa (DMS). Los resultados demuestran que las secuencias de cultivos tuvieron influencia sobre la abundancia y la acumulación de peso seco, especialmente la secuencia maíz-fríjol, la cual muestra disminución en las variables mencionadas La secuencia fríjol-fríjol bajo el control cultural presentó el mayor peso seco total de malezas (348.2 g /m2). La secuencia maíz-fríjol presentó mayor número de plantas por unidad de área (31.4) y mayor número de vainas por planta (9.4) en los tres años de estudio. Los rendimientos del grano fueron mayores en la secuencia maíz-fríjol en los tres controles de malezas, siendo el control químico el que mayor valor presentó con 1538.2 kg/ha. La secuencia fríjol-fríjol obtuvo rendimientos bajos principalmente por la competencia de malezas y la incidencia de enfermedades fungosas. El control cultural obtuvo el menor rendimiento con 619 kg/ha. El control mecánico presentó el mejor beneficio neto, seguido por el control químico y luego el cultural. Los buenos rendimientos obtenidos en el control químico permiten la compensación de los altos costos que significa la utilización de estos productos químicos. En 1995 se obtuvo el mayor beneficio neto seguido por 1996 y luego 1994. Este comportamiento se debió principalmente al precio de venta del fríjol al momento de la cosecha y a los rendimientos obtenidos en cada año. Estos resultados muestran diferencia entre los factores en estudio, siendo la precipitación la que más influencia tuvo en las diferencias entre los años.

La articulación textual en los "Progumnásmata" de Nicolao de Mura

[ES]En este trabajo se estudia el uso de los marcadores del discurso y del asíndeton como medios de articulación textual entre los diversos enunciados que constituyen los "Progumnásmata" de Nicolao. Este estudio permite observar si existen diferencias entre las dos partes que componen la edición de Felten y si el uso de partículas de Nicolao es diferente del que hacen los demás autores de "Progumnásmata".

Ahozkotasunaren irakaskuntza bigarren hezkuntzako testuliburuetan

[EN]Traditionally writing skills have been given priority in language teaching and so, oral skills have been put aside. However, during the last years many voices have asserted the importance of oral skills. Therefore, they claim that oral language teaching must be emphasized at school. Also, the necessity of strengthening oral language is shown in the new curriculum. Nevertheless, those intentions are reflected in very different ways in textbooks. In this work we have looked into the treatment that oral language is given in teaching materials because, in our opinion, textbooks are one of the most important tools for teachers. The facts show that the importance given to oral language and the exercises and tools needed to work that skill are very different from one publishing house to another. Besides, we have confirmed that all the textbooks don’t satisfy the requirements proposed in the Basque official curriculum (e.g. didactic sequences) or that the approach to the text or the way to work with it are not always what they should be. Therefore, it is obvious that we have still a long way in the field of oral language and specially in the way of teaching oral skills

Prototipismo textual, audiovisual y traductológico: una propuesta integradora

Raquel Merino Álvarez, José Miguel Santamaría, Eterio Pajares (eds.)

Exploring Semantic Textual Similarity

[EN]Measuring semantic similarity and relatedness between textual items (words, sentences, paragraphs or even documents) is a very important research area in Natural Language Processing (NLP). In fact, it has many practical applications in other NLP tasks. For instance, Word Sense Disambiguation, Textual Entailment, Paraphrase detection, Machine Translation, Summarization and other related tasks such as Information Retrieval or Question Answering. In this masther thesis we study di erent approaches to compute the semantic similarity between textual items. In the framework of the european PATHS project1, we also evaluate a knowledge-base method on a dataset of cultural item descriptions. Additionaly, we describe the work carried out for the Semantic Textual Similarity (STS) shared task of SemEval-2012. This work has involved supporting the creation of datasets for similarity tasks, as well as the organization of the task itself.