Brisbane Evidence-Based Language Test

Rohde, Alexia; Doi, Suhail A.R.; Worrall, Linda; Godecke, Erin; Farrell, Anna; O’Halloran, Robyn; McCracken, Molly; Lawson, Nadine; Cremer, Rebecca; Wong, Andrew L.

doi:10.1037/t86337-000

Cited by 2 publications

(2 citation statements)

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“…There are several published collections of stimuli and assessment procedures that aim to provide a relatively comprehensive assess ment of aphasia. These include the BDAE (Goodglass et al, 2001), the Multilingual Aphasia Examination (Benton & Hamsher, 1983), Western Aphasia Battery Revised (WABR), Brisbane EvidenceBased Language Test (EBLT; Rohde et al, 2022), Psycholinguistic Assessment of Language Processing in Aphasia (PALPA; Kay et al, 1996), and the Comprehensive Aphasia Test (CAT; Swinburn et al, 2004). The BDAE is the oldest and perhaps most widely used battery, and both the BDAE and the WABR are designed to facilitate classification of the aphasic syndromes.…”

Section: Aphasia Assessment Batteriesmentioning

confidence: 99%

Aphasia.

Sabsevitz,

Pillay

2024

Clinical Neuropsychology: A Pocket Handbook for Assessment (4th Ed.).

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Language refers to a system of communication that utilizes a variety of arbitrary symbols to convey meaning. Aphasia is a neurological condition whereby language processing is disturbed as a result of regional brain dysfunction. Aphasia can result in disturbance of language comprehension, production, or both, and can affect the ability to read and write. No single behavioral presentation is asso ciated with aphasia; rather, depending on the location and size of the underlying brain lesion, there are constellations of impairments that vary in severity and can cluster into one of the recognized syndromes.Aphasia can be caused by a wide variety of neurological con ditions. The most common cause of aphasia is stroke; however, traumatic brain injury, brain tumor, abscess or infection, and certain neurodegenerative conditions (e.g., primary progressive aphasia, Alzheimer's disease) can also cause aphasia. Transient aphasia can occur during or following a seizure (e.g., postictal aphasia) in the dominant hemisphere or during a transient ischemic attack or

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Section: Aphasia Assessment Batteriesmentioning

confidence: 99%

Aphasia.

Sabsevitz,

Pillay

2024

Clinical Neuropsychology: A Pocket Handbook for Assessment (4th Ed.).

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“…The problem of consistency in giving scores to students' answers can arise from the same evaluator or different evaluators [19]. Inconsistent assessment of answers from the same evaluator often occurs when evaluations are carried out at different times, whereas other evaluators can also provide their subjectively different scores.…”

Section: Related Workmentioning

confidence: 99%

Evaluating the Impact of Sentence Tokenization on Indonesian Automated Essay Scoring Using Pretrained Sentence Embeddings

Chamidah,

Yulianti,

Budi

2023

RIA

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Automated Essay Scoring (AES) systems are designed to expedite the assessment process, where human scoring is frequently slow and subject to inconsistencies and inaccuracies. This study, therefore, investigates the role of sentence tokenization in the performance of Indonesian Automated Essay Scoring, given that Natural Language Processing (NLP) techniques are requisite in AES to handle student responses that present identical semantic meanings but vary in length. A distinct approach was adopted in which full answers were not vectorized; instead, they were fragmented into sentences prior to vectorization. This method was deemed potentially more effective due to the high probability of discrepancies in sentence order between reference and student responses. Sentence embeddings, which encapsulate a sentence as a sole vector, were utilized. Pretrained SBERT-based sentence embeddings were employed to vectorize sentences from both reference answers and student responses, serving as semantic features for the Siamese Manhattan LSTM (MaLSTM) model. The MaLSTM model possesses the ability to process two inputs and evaluate their similarity using the Manhattan distance metric and use this similarity value as a predictive scoring output. This score was subsequently compared to human scores using the Root Mean Square Error (RMSE) and Pearson Correlation. Interestingly, sentence embeddings without tokenization slightly outperformed those with sentence splitting, as evidenced by a 0.61% improvement in RMSE and a 0.01 increase in Pearson Correlation. The results obtained indicate that sentence tokenization, as applied to the Indonesian Automated Essay Scoring dataset, does not have a notable impact on essay scoring performance. Therefore, it may be concluded that the application of sentence tokenization is not a necessary step in this dataset's text-processing phase of AES.

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Brisbane Evidence-Based Language Test

Cited by 2 publications

References 0 publications

Aphasia.

Aphasia.

Evaluating the Impact of Sentence Tokenization on Indonesian Automated Essay Scoring Using Pretrained Sentence Embeddings

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