Errors that occur during the process of learning a foreign language serve as a measure of the learner’s acquisition and development of the target language. Corder [1] claimed that the errors made by learners can be a learning strategy for acquiring a new language, rather than simply a negative signal. Through error analysis, learners can identify the areas where acquisition is not going well and find the direction for learning [2]. In addition, error analysis, which explains the accuracy levels, is used to predict test takers’ proficiency levels. Accuracy, along with fluency and complexity, has been used as the primary predictor of language proficiency ^[3][4][3,4]. With the increasing importance of automated language assessment, these linguistic features are likely to be included in automated speaking assessments, and they can be used to provide adaptive feedback to test takers or language learners [5].

Numerous studies have emphasized the use of error analysis as a means of improving students’ foreign language learning, with a particular focus on identifying the challenging aspects that students may encounter ^[6][7][8][6,7,8]. While most of these studies have concentrated on errors made in writing, only a small amount of research has been conducted on error analysis of the speaking of English language learners [9]. Furthermore, these studies rarely considered the topics of the input used.

In performance-based oral communication tests, prompts or inputs affect examinees’ performances, leading to variation in proficiency scores ^[10][11][10,11]. While these studies focused on the effect of tasks on test takers’ performance in general, they did not examine specific language variations. For example, Won [12] investigated the effects of task complexity on test takers’ linguistic outputs, such as the subordination index [13], Guiraud index [14], number of errors per AS-unit [15], speech rate, repairs, filled pauses, and their related proficiency scores. However, little attention has been paid to the effect of test inputs on the types of errors that test takers make in their responses in speaking tests.

2. Error Analysis

Error analysis (EA) is a process that involves carefully analyzing the errors made by language learners to understand the process of second-language learning and to suggest suitable teaching and learning strategies and remedial measures necessary for the target language. The reason is that errors made by language learners have been viewed as a natural part of the language acquisition process, rather than a sign of a language filled with grammatical mistakes. Errors are inadequacies that originate from a lack of linguistic knowledge and are systematic, while mistakes are seen as performance-related errors [1]. Errors cannot be self-corrected until the learner receives more pertinent input, and errors, not mistakes, are important elements that have contributed to language acquisition research ^[16][17][16,17]. EA differs from contrastive analysis (CA) in that EA focuses on examining the mistakes made by students and identifying areas where improvement is needed while CA involves analyzing the differences between two languages to identify areas where learners might encounter difficulties [18]. Observing learner errors can thus help identify the language system being used and this is crucial for several reasons. First, error analysis allows teachers to evaluate how far a learner has progressed and what needs to be taught as they move forward. Second, learner errors provide researchers with evidence of how a language is learned and the strategies used by learners. Third, errors are a valuable tool for learners themselves in achieving target language proficiency [18]. However, error analysis also has several weaknesses. One significant problem is the difficulty of reliably classifying errors based purely on linguistic information. Moreover, error analysis is limited to analyzing the output of the learner, and cannot adequately consider receptive skills. The avoidance strategy, when a student decides not to use a form they are not confident in, is also not taken into account in error analysis ^[19][20][19,20].

3. Surface Strategy Taxonomy

Dulay, Burt, and Krashen [17] proposed a surface strategy taxonomy that categorizes errors into four categories: omission, addition, misformation, and misordering. These categories are based on the possibility of changing the surface structure of a morpheme or verb. Omission errors occur when a morpheme or word is missing from a well-formed utterance [17]. This omission can occur with both content morphemes (e.g., nouns, verbs, adjectives, adverbs) and grammatical morphemes (e.g., function words), which happens more frequently ^[17][21][17,21]. For example, the sentence “I (am) wondering if it is really possible things” lacks the BE-verb after I, and the sentence “there is no idea to say (about) it” lacks the function word about. Addition errors occur when there is the presence of any morpheme or word that should not appear in a well-formed utterance. For example, the preposition for is wrongly inserted in the sentence “I read essay about for my future”. Misformation errors occur when an incorrect form of the morpheme or structure is used. For example, the expression “taking a house” is incorrectly used instead of “buying a house” in the sentence “we can save some money for taking a house.” These errors are more common in the later phases of L2 acquisition [17]. Misordering errors occur when there is a wrong placement of a morpheme or collection of morphemes in a well-formed utterance [17]. For example, in the sentence “we cannot anymore live on this planet”, the expression “anymore live on this planet” should be reordered to “live on this planet anymore”.

4. Previous Studies on Error Analysis in Spoken English

Most of the studies on error analysis of learners of English are based on written materials ^[9][22][9,22]. Compared to written data, error analysis of spoken data is more challenging because it requires transcription. Error analysis of speaking data can be broadly classified into two types: (a) classification of errors according to grammatical elements and/or (b) classification of errors according to the surface strategy taxonomy (e.g., omission, addition, misformation, and misordering; Dulay, Burt and Krashen [17]). There have been several studies that used the classification of errors made by Korean learners of English based on grammatical categories. Chin [23] investigated the types of spoken errors produced by low-level Korean learners of English. Her study revealed that errors related to the use of noun phrases and verb phrases were most frequently made in picture description tasks. Among noun phrase-related errors, article use errors were most common, followed by noun form errors. Kim [24] analyzed the types of spoken errors made by Korean college students majoring in secretarial studies in English-speaking tests using simulated telephone conversations. The study identified six major error categories, with the most frequent errors being noun phrase errors, followed by verb phrase errors, clause/sentence structure errors, adjective phrase errors, and prepositional phrase errors. Among the subcategories of errors, errors in the use of articles were most frequently found, followed by errors in word order, how to address others, verb tense choice, subject or verb omission, and BE-verb misuse. Kim, et al. [25] investigated spoken errors made by Korean high school students, examining how errors vary by English speaking proficiency level. The study found a high frequency of errors related to verb omission, verb addition, verb choice, subject–verb agreement, and the use of -ing across all levels of learners. However, the use of the -ing form differed between high-proficiency-level students (e.g., use of the -ing form where unnecessary) and low-proficiency-level students (e.g., omitting -ing where necessary). Ahn [26] studied the types and frequency of grammar errors made by Korean college students while communicating with their peers in English and the impact these errors had on communication breakdown. She adopted the grammatical error categories used in Chin [23] and Kim [24], and found that errors related to noun phrases and verb phrases were the most prevalent. The frequency hierarchy of error subcategory was relevant to articles, verbs, prepositions omitted, word misuse, and pronouns, in this order. Conversation analysis showed that grammar errors rarely caused communication problems. Noh [27] and Yoon [21] analyzed the spoken errors produced by Korean college students in speaking tests using a surface strategy classification: addition, omission, misformation, and misordering errors [17]. Noh [27] reviewed errors in the speech of L2 English learners to identify error types and causes, including unnatural expression errors and communication disorder errors, using the surface strategy classification. This study found that semantic errors were the most prominent, followed by grammatical errors such as in the choice of prepositions and parts of speech. Yoon [21] investigated and classified the grammatical errors made by Korean EFL students in the TOEIC speaking test according to the surface strategy classification. She found that omission errors were the most prevalent (74.9%), followed by misformation (19.9%) and misordering (1.7%). Several studies have used both grammatical elements and the surface strategy taxonomy as the main criteria for error classification. Back [28] analyzed preposition errors made by Korean EFL learners in speaking and writing, as well as the factors that caused these errors. The results showed that omission (about 40%) was the most prevalent error in the speaking corpus, followed by misformation (34%) and addition errors. In the case of preposition errors, on the other hand, addition (28.3%) was the most salient error, followed by omission (19.7%) and misformation (10.1%). Son and Chang [29] conducted a comprehensive analysis of the grammatical errors exhibited by Korean university students during their English speaking activities. Moreover, they examined the variations in error patterns based on the students’ levels of proficiency. In the study, participants were asked to describe a picture and respond to a speaking prompt. The study categorized the grammatical errors into six groups with 45 subgroups. Overall, the results found that noun and verb phrases had the highest error rates. Grammatical errors in noun phrases were the most frequent, followed by verb phrases, preposition phrases, sentence structure, and adjectives. The error analysis by proficiency level showed that beginner-level learners made more grammatical errors overall than intermediate learners. More specifically, beginners had the most subject–verb agreement errors, while intermediate learners had more awkward expressions. Choi [9] analyzed the English speaking errors and error perceptions of Korean learners. The study used college students’ TOEIC speaking test responses and transcribed their audio clips. The transcripts were then coded with the six grammatical errors (e.g., noun phrase, verb phrase, number/price unit, clause/sentence structure, prepositional phrase, adjective phrase, others) introduced in Chin [23] and Kim [24]. These six categories were subdivided into omission, addition, misformation, and lexical errors as proposed by Dulay, Burt and Krashen [17], Noh [27], and Yoon [21]. Overall, the studies investigated various grammatical error types and their relative frequencies in the spoken English data of Korean learners of English. However, many of the studies focused primarily on error frequencies without considering the learners’ proficiency levels. While Kim, Pae, Hwang and Rhee [25] and Son and Chang [29] took proficiency levels into account when analyzing error types and their frequencies, they did not investigate whether each error solely affected the proficiency level or if all errors collectively affected students’ proficiency levels. Furthermore, these studies rarely considered how prompts (or inputs) affected the types and frequency of errors produced by learners.