Promoción del ritmo de estudio por feedback colectivo de progreso en trabajos prácticos

La mejora en el ritmo de estudio es una de las preocupaciones centrales de los docentes, en particular en ciencias básicas y computación. En particular, el desarrollo de trabajos prácticos dentro y fuera del aula es considerado una actividad clave de aprendizaje. En este trabajo, describimos un estudio exploratorio realizado en un curso introductorio de programación, en el cual se hizo visible cuántos ejercicios llevaban resueltos los alumnos, clase a clase, para la guía correspondiente. Los resultados muestran significativas mejoras relativas (comparando guía inicial con guía final) a medida que avanza el curso, en la cantidad de ejercicios resueltos. También realizamos una contrastación de los datos recogidos con los resultados del examen al final del período estudiado. En el cierre, describimos el alcance del estudio, los mecanismos para repetirlo y perspectivas de futuros trabajos.IV Workshop de Innovación en Educación en Informática (WIEI)Red de Universidades con Carreras en Informática (RedUNCI

Promoción del ritmo de estudio por feedback colectivo de progreso en trabajos prácticos

La mejora en el ritmo de estudio es una de las preocupaciones centrales de los docentes, en particular en ciencias básicas y computación. En particular, el desarrollo de trabajos prácticos dentro y fuera del aula es considerado una actividad clave de aprendizaje. En este trabajo, describimos un estudio exploratorio realizado en un curso introductorio de programación, en el cual se hizo visible cuántos ejercicios llevaban resueltos los alumnos, clase a clase, para la guía correspondiente. Los resultados muestran significativas mejoras relativas (comparando guía inicial con guía final) a medida que avanza el curso, en la cantidad de ejercicios resueltos. También realizamos una contrastación de los datos recogidos con los resultados del examen al final del período estudiado. En el cierre, describimos el alcance del estudio, los mecanismos para repetirlo y perspectivas de futuros trabajos.IV Workshop de Innovación en Educación en Informática (WIEI)Red de Universidades con Carreras en Informática (RedUNCI

Promoción del ritmo de estudio por feedback colectivo de progreso en trabajos prácticos

La mejora en el ritmo de estudio es una de las preocupaciones centrales de los docentes, en particular en ciencias básicas y computación. En particular, el desarrollo de trabajos prácticos dentro y fuera del aula es considerado una actividad clave de aprendizaje. En este trabajo, describimos un estudio exploratorio realizado en un curso introductorio de programación, en el cual se hizo visible cuántos ejercicios llevaban resueltos los alumnos, clase a clase, para la guía correspondiente. Los resultados muestran significativas mejoras relativas (comparando guía inicial con guía final) a medida que avanza el curso, en la cantidad de ejercicios resueltos. También realizamos una contrastación de los datos recogidos con los resultados del examen al final del período estudiado. En el cierre, describimos el alcance del estudio, los mecanismos para repetirlo y perspectivas de futuros trabajos.IV Workshop de Innovación en Educación en Informática (WIEI)Red de Universidades con Carreras en Informática (RedUNCI

Rise of the machines? The evolving role of Artificial Intelligence (AI) technologies in high stakes assessment

Our world has been transformed by technologies incorporating artificial intelligence (AI) within mass communication, employment, entertainment and many other aspects of our daily lives. However, within the domain of education, it seems that our ways of working and, particularly, assessing have hardly changed at all. We continue to prize examinations and summative testing as the most reliable way to assess educational achievements, and we continue to rely on paper-based test delivery as our modus operandi. Inertia, tradition and aversion to perceived risk have resulted in a lack of innovation (James, 2006), particularly so in the area of high-stakes assessment. The summer of 2020 brought this deficit into very sharp focus with the A-level debacle in England, where grades were awarded, challenged, rescinded and reset. These events are potentially catastrophic in terms of how we trust national examinations, and the problems arise from using just one way to define academic success and one way to operationalize that approach to assessment. While sophisticated digital learning platforms, multimedia technologies and wireless communication are transforming what, when and how learning can take place, transformation in national and international assessment thinking and practice trails behind. In this article, we present some of the current research and advances in AI and how these can be applied to the context of high-stakes assessment. Our discussion focuses not on the question of whether we should be using technologies, but on how we can use them effectively to better support practice. An example from one testing agency in England using a globally popular test of English that assesses oral, aural, reading and written skills is described to explain and propose just how well new technologies can augment assessment theory and practice

Increasing the effectiveness of automated assessment by increasing marking granularity and feedback units

Computer-based assessment is a useful tool for handling large-scale classes and is extensively used in the automated assessment of student programming assignments in Computer Science. The forms that this assessment takes, however, can vary widely from simple acknowledgement to a detailed analysis of output, structure and code. This study focusses on output analysis of submitted student assignment code and the degree to which changes in automated feedback influence student marks and persistence in submission. Data was collected over a four year period, over 22 courses but we focus on one course for this paper. Assignments were grouped by the number of different units of automated feedback that were delivered per assignment to investigate if students changed their submission behaviour or performance as the possible set of marks, that a student could achieve, changed. We discovered that pre-deadline results improved as the number of feedback units increase and that post-deadline activity was also improved as more feedback units were available.Nickolas Falkner, Rebecca Vivian, David Piper and Katrina Falkne

Toward a digital future of curriculum, pedagogy & assessment

In the last three decades, digital technologies have become an integral part of our lives, societies and education systems worldwide. Hence it is essential that educators can teach and incorporate technologies in their teaching practices (Yadav & Lachney, 2022). By doing so, we can ‘future-proof’ the upcoming generations who will learn with the aid of constantly evolving technologies, need to understand the impact of technologies on society, and must use technologies to showcase creativity and innovation in all aspects of life. The Covid-19 pandemic and subsequent lockdowns since early 2020 have accelerated the incorporation of technology in education. Webmediated education has been introduced to replace or supplement traditional offline modes of teaching and learning. The willingness to adopt and experiment with digital technologies in education, including online learning software, video conferencing tools, virtual tutoring, and learning apps, continues to grow. We have chosen the following blog posts for this edition of BERA Bites because they provide valuable insights into curriculum, pedagogy and assessment, and suggest further lines of inquiry for research and practice. The authors address important issues impacting education and offer ideas for developing a shared vision for the digital future of education

Beyond Automated Assessment: Building Metacognitive Awareness in Novice Programmers in CS1

The primary task of learning to program in introductory computer science courses (CS1) cognitively overloads novices and must be better supported. Several recent studies have attempted to address this problem by understanding the role of metacognitive awareness in novices learning programming. These studies have focused on teaching metacognitive awareness to students by helping them understand the six stages of learning so students can know where they are in the problem-solving process, but these approaches are not scalable. One way to address scalability is to implement features in an automated assessment tool (AAT) that build metacognitive awareness in novice programmers. Currently, AATs that provide feedback messages to students can be said to implement the fifth and sixth learning stages integral to metacognitive awareness: implement solution (compilation) and evaluate implemented solution (test cases). The computer science education (CSed) community is actively engaged in research on the efficacy of compile error messages (CEMs) and how best to enhance them to maximize student learning and it is currently heavily disputed whether or not enhanced compile error messages (ECEMs) in AATs actually improve student learning. The discussion on the effectiveness of ECEMs in AATs remains focused on only one learning stage critical to metacognitive awareness in novices: implement solution. This research carries out an ethnomethodologically-informed study of CS1 students via think-aloud studies and interviews in order to propose a framework for designing an AAT that builds metacognitive awareness by supporting novices through all six stages of learning. The results of this study provide two important contributions. The first is the confirmation that ECEMs that are designed from a human-factors approach are more helpful for students than standard compiler error messages. The second important contribution is that the results from the observations and post-assessment interviews revealed the difficulties novice programmers often face to developing metacognitive awareness when using an AAT. Understanding these barriers revealed concrete ways to help novice programmers through all six stages of the problem-solving process. This was presented above as a framework of features, which when implemented properly, provides a scalable way to implicitly produce metacognitive awareness in novice programmers

Enabling Wide-Scale Computer Science Education through Improved Automated Assessment Tools

There is a proliferating demand for newly trained computer scientists as the number of computer science related jobs continues to increase. University programs will only be able to train enough new computer scientists to meet this demand when two things happen: when there are more primary and secondary school students interested in computer science, and when university departments have the resources to handle the resulting increase in enrollment. To meet these goals, significant effort is being made to both incorporate computational thinking into existing primary school education, and to support larger university computer science class sizes. We contribute to this effort through the creation and use of improved automated assessment tools.To enable wide-scale computer science education we do two things. First, we create a framework called Hairball to support the static analysis of Scratch programs targeted for fourth, fifth, and sixth grade students. Scratch is a popular building-block language utilized to pique interest in and teach the basics of computer science. We observe that Hairball allows for rapid curriculum alterations and thus contributes to wide-scale deployment of computer science curriculum. Second, we create a real-time feedback and assessment system utilized in university computer science classes to provide better feedback to students while reducing assessment time. Insights from our analysis of student submission data show that modifications to the system configuration support the way students learn and progress through course material, making it possible for instructors to tailor assignments to optimize learning in growing computer science classes

Optical Character Recognition based approach for automatic Image Marking Process

In today's world, programming teachers perform tedious tasks, which are time consuming; for instance, preparing and marking daily assignments, preparing and marking programming projects, preparing and marking short exams, etc. These tasks distract programming teachers from fulfilling their key role – teaching. Therefore, using automated marking approach with ability to communicate with students is highly desirable. Despite the existing approaches for automated student marking, there is still a need for more improvement. An automated program marking approach is proposed in this study based on a proposal by iMarking®. This approach automates the process of marking and assignments submission and facilitates the communication between teachers and students by designing and implementing a web-based application. In addition, the proposed approach adopts Optical Character Recognition (OCR) to extract the text from images to be evaluated using novel evaluation metrics. The novel evaluation metrics are formulated based on observation and experiment and aim to calculate the matching similarity and mismatching percentage of the submitted student answers when compared with the optimal answers. Evaluation results from a sample of 100 different programming questions show that the proposed approach is efficient in automatically marking the student answers with 100% accuracy. Furthermore, it is found to be time saving – approximately 197 seconds for marking ten questions – which is in line with the objective of creating a more efficient system for teachers