Enhancing English Past Tense Acquisition: Comparative Effects of Structured Input, Referential, and Affective Activities

Abstract

This study investigates the impact of structured input, referential activities, and affective activities on English simple past tense acquisition in a second language (L2). Thirty-three participants from a senior high school were divided into four groups based on the pretest–posttest design: referential only, affective only, a combination of both, and a control group. A self-paced reading (SPR) test was used to measure accuracy and response times to evaluate the effectiveness of these instructional strategies. Structured input and referential tasks enhance grammatical acquisition more rapidly and accurately than affective-only treatments or controls, showing the beneficial effects of structured input on grammar acquisition. The results emphasized the importance of designing instructional strategies that address specific processing challenges in L2 learning by focusing on form–meaning connections. By demonstrating differential impacts of structured input activities on grammatical learning and processing efficiency, the research contributes to the field of second language acquisition. The SPR method was selected for its ability to capture subtle, immediate differences in processing at the word level, its suitability for controlled classroom-based online administration, and its established validity in L2 processing research. Unlike other methods, SPR allows precise measurement of reaction times for specific sentence components, isolating processing effects of the target grammatical form while minimizing the influence of explicit knowledge.

1. Introduction

The difficulty that L2 learners face in acquiring inflectional morphologies, such as the English past tense “-ed”, is acknowledged by scholars, but their perspectives on its origins diverge. Some scholars argue that the challenge arises from the inherent complexity of inflectional systems, which can be difficult to internalize for learners whose first language (L1) lacks similar structures (Ellis, 2006). Others suggest that the difficulty is rooted in the cognitive demands of processing and producing morphologically inflected forms in real-time communication (DeKeyser, 2014). Additionally, there are perspectives that attribute this struggle to insufficient exposure and practice with the target language’s morphological patterns in naturalistic settings (Krashen, 1985). There are theories that suggest that the problem is either caused by performance issues or by a lack of competence at the representational level. In their MSIH (Missing Surface Inflection Hypothesis), Prévost and White (2000) propose that language learners with limited performance possess unconscious grammatical knowledge. This idea is echoed in Sorace (1985) and Sharwood-Smith (1986), who highlight a latency between acquiring linguistic features and gaining control over them, attributing errors to the gradual development of procedural knowledge needed to leverage implicit knowledge effectively. In contrast, scholars like Gass (1999) and VanPatten (2015) suggest that such difficulties stem from incomplete acquisition rather than retrieval difficulties, as shown by morphological errors in proficient learners and different responses to grammatical violations in sentence processing studies. Implicit knowledge refers to the subconscious understanding and use of language, which is ac-quired through exposure and practice, often without conscious awareness. Explicit knowledge, on the other hand, involves a conscious understanding of language rules and structures, typically gained through formal instruction. In language acquisition, implicit knowledge is crucial for fluency and spontaneous communication, while explicit knowledge can aid in learning and correcting errors, particularly in the early stages of language learning.

While prior studies have offered valuable insights, there remains a notable gap in understanding the immediate, online processing effects of different types of structured input activities, particularly for Chinese EFL (English as a foreign language) learners whose first language lacks tense inflection. Addressing this gap, the present study examines how referential, affective, and combined structured input activities influence the acquisition of the English simple past tense, using self-paced reading to capture real-time processing. This approach not only builds on VanPatten’s Input Processing Theory but also offers pedagogical insights for designing more effective grammar instruction.

Aims of the Study

Using VanPatten’s Input Processing Theory, this study examines how structured input activities, both referential and affective, influence the acquisition of the English simple past tense. VanPatten’s (1996, 2004) principles of lexical salience and processing constraints explain why learners often overlook grammatical markers like the past tense “-ed”. Structured input enhances processing efficiency, thereby improving language intake and learning, according to Benati (2023) and others. To address gaps in current methodologies relying on offline testing, this study employs online measurement tools, specifically self-paced reading tests, to evaluate the immediate effects of different structured input strategies on Chinese learners’ acquisition of English past tense.

To be specific, this study aimed to extend existing research by:

• Providing additional empirical evidence on how structured input influences Chinese EFL learners’ processing of English past tense markers.
• Comparing the immediate effects, in terms of accuracy and response time, of referential versus affective structured input on mastering these markers.

While prior studies have examined referential and affective structured input using offline methods, this study employs SPR to assess deep processing in L2 learners more reliably. SPR was chosen for its capacity to detect subtle, real-time processing differences at the word level, its adaptability to controlled online classroom settings, and its proven reliability in L2 research (Jegerski, 2013; Marsden et al., 2018). Compared to alternative techniques, SPR facilitates precise reaction time measurements for targeted sentence components, isolating the impacts of the focal grammatical feature while mitigating explicit knowledge influences. This method captures millisecond-level reaction times to specific sentence regions, enabling precise isolation of grammatical processing effects with minimal reliance on conscious rule recall. The current study assessed the following:

• Accuracy in identifying English past tense forms.
• Response time for correct recognition.
• Processing time for verbs in target sentences.

The research also investigated how different structured input strategies—referential only, affective only, and a combination of both—affect English language learning outcomes among Chinese L1 speakers. The focus is on accurately interpreting sentences with English past tense forms and the efficiency of processing these forms at the word level.

The study posed three research questions:

• Does exposure to different structured input treatments (referential, affective, or combined) equally improve L2 learners’ accuracy in interpreting English past tense forms?
• Does exposure to these treatments equally enhance learners’ response times in interpreting these forms?
• Do these treatments result in similar processing times for English past tense forms at the word level?

2. Theoretical Background

2.1. An Input Processing Perspective

VanPatten’s (1996, 2004, 2015) Input Processing Theory explains how language input is processed and internalized by learners by concentrating on two key concepts:

• Internal Mechanisms for Information Processing: Learners rely on innate cognitive mechanisms to interpret and integrate information they receive from the language environment. These mechanisms, rooted in working memory and attentional processes (Cowan, 2001), play a critical role in transforming input into intake—the information that learners actually acquire and internalize.
• Processing Constraints: This concept recognizes that despite robust internal mechanisms, humans have limited capacities for information processing. Cognitive constraints on memory and attention can impact the efficiency and selectivity of language processing, influencing which elements of the input learners attend to and internalize (Cowan, 2001; VanPatten, 2015).

These core principles clarify the intricacies of language acquisition and the difficulties learners encounter with the extensive input they receive. By comprehending these mechanisms and limitations, educators can develop instructional strategies that align with learners’ innate processing abilities, thereby improving the efficiency and effectiveness of language learning.

Working memory and attentional constraints often limit the amount of information L2 learners can process (Cowan, 2001). VanPatten defines intake as the portion of language data processed and stored in learners’ working memory. Learners must actively process this data for it to become part of their internal systems. Language development depends on the “detection” process, in which language data is registered in working memory, enabling further processing. Tomlin and Villa (1994) emphasized the importance of detection in language development. Attentional resources are consumed during this detection process, which interferes with the processing of other information.

VanPatten’s research examines how learners process language input, identifying which elements are processed and which are overlooked. The aim of his research is to provide insights critical to the development of more effective methods for teaching languages, by understanding the cognitive mechanisms and constraints that govern these interactions.

The landscape of language learning has evolved with technology, providing learners with extensive access to authentic language input through digital devices (Chapelle, 2001). Despite this, language acquisition remains a slow process, similar in pace to a child’s mastery of their first language. Corder (1967) noted that not all input is processed by learners due to their limited processing capabilities. As part of learners’ interlanguage system, only a subset of the input, called “intake” by VanPatten et al. (2020), can be directly connected to meaning during real-time comprehension. The importance of this subset is that learners’ internal mechanisms decide which input gets processed and which is ignored, highlighting the need for theories that explain these constraints and help learners make connections between form and meaning.

2.2. The Theory of Input Processing

As described by VanPatten, the Input Processing Theory examines how L2 learners derive their intake from language input, specifically how linguistic forms and features are processed when meaning is the primary focus. In this theory, two pivotal questions are addressed:

• What are the reasons for processing only a small part of the input?
• What determines which elements in the input are processed and which are not?

A semantic connection between form and meaning is forged during real-time comprehension of language input, according to VanPatten (2004). The learner’s ability to detect certain grammatical features is constrained by his or her limited working memory and attentional capacity.

• Core Principles of Input Processing

• The Primacy of Meaning Principle: This principle asserts that learners prioritize the overall meaning of language input over grammatical forms. It suggests that language instruction should focus on meaningful communication to ensure that learners grasp the semantic content before the structural details.

• Sub-strategies of the Primacy of Meaning Principle

• Content before Form: Learners first focus on content words like nouns and verbs, which carry significant semantic information, before other grammatical elements.
• Lexical over Grammatical Items: Learners process lexical items before grammatical ones when both encode the same semantic information, as lexical items are more directly linked to meaning.
• Non-redundant before Redundant Forms: Forms that provide unique, necessary information are prioritized over those that might repeat or elaborate on already understood content.
• Meaningful Morphology First: Morphological forms that contribute meaningfully to the overall message are processed before less significant forms.
• Allocation of Processing Resources: Learners manage cognitive resources to handle linguistic complexity based on the demands of the input.
• Processing Order within Sentences: Elements at the beginning of a sentence are processed first, followed by those at the end, and finally those in the middle, reflecting the cognitive ease of integrating information presented at these positions.

Implications for Language Teaching

Understanding these principles can significantly enhance language teaching and curriculum design (VanPatten, 2014). Instruction that aligns with natural processing tendencies, such as emphasizing meaningful communication and presenting new language forms within meaningful contexts, can improve learning outcomes. Additionally, structuring input to highlight content words and meaningful grammatical forms can aid learners in more efficiently processing and retaining new language (VanPatten, 2014).

VanPatten’s theory provides a robust framework for exploring how language acquisition occurs and informs effective teaching strategies that leverage the cognitive processes involved in learning a language. By emphasizing meaning and strategically integrating form within meaningful contexts, educators can help learners develop both linguistic competence and communicative proficiency.

These insights are reformulated into six sub-principles, which detail how learners prioritize and process different aspects of language input to maximize comprehension and intake. Each sub-principle targets a specific aspect of language processing, collectively providing a comprehensive understanding of how L2 learners navigate language input. This holistic approach deepens our understanding of language processing and, meanwhile, enhances language teaching effectiveness by aligning instructional practices with natural processing tendencies.

3. Processing Instruction

The purpose of processing instruction is to improve learners’ understanding and retention of input by engaging them in structured practice based on VanPatten’s Input Processing Theory. By engaging in this practice, learners are redirected from default processing strategies to more focused attention on specific, meaningful elements within sentences, resolving the processing challenges discussed in previous theoretical articles. It improves learners’ ability to create correct form–meaning mappings, which is crucial for achieving proficiency in a second language by enabling them to navigate the complexities of language input better.

Benati (2021) identifies several grammatical forms impacted by the Primacy of Meaning Principle, including tense markers, subject–verb agreement, aspectual markers, mood expressions, subjunctive, adjective agreement, and case markers. Research by Lee and Benati (2009) confirms that PI significantly alters default processing strategies among L2 learners from various linguistic backgrounds, with structured input practice playing a key role in forming initial connections between linguistic forms and their meanings.

3.1. Structured Input as the Main Component of Processing Instruction

Structured input plays a pivotal role in processing instruction because it addresses the specific challenges that L2 learners face when processing input in their native languages. There are two main components (see

Table 1. Components of processing instruction.

Component	Description
Explicit Information	Information about nonoptimal processing strategies
Structured Input	- Referential activities - Affective activities

):

• Explicit Information: Learners are directly informed about nonoptimal processing strategies that hinder their comprehension of certain grammatical forms or structures.
• Structured Input Activities: Activities using referential and affective input are designed to assist learners in their understanding of specific grammatical forms.

Structured input manipulates input in ways that make learners reliant on form and structure to derive meaning, or it highlights these elements to enhance learner attention (VanPatten, 2002).

Principles for Effective Structured Input Activities (Lee & VanPatten, 1995):

• Introduce Elements Individually: To avoid overwhelming learners, introduce grammatical elements one at a time.
• Focus on Meaning: Center activities around understanding meaning to ensure that form–meaning connections are made.
• Progress from Simple to Complex: Start with individual sentences and gradually move to longer, coherent texts.
• Incorporate Multiple Modalities: Use both spoken and written forms of language to reinforce learning.
• Active Learner Engagement: Require learners to manipulate or respond to the input actively.
• Adapt to Learner Strategies: Design activities considering the processing strategies learners are likely to use.

Types of Structured Input Activities:

• Referential Activities: These tasks require learners to respond (e.g., yes/no answers) based on their understanding of the grammatical forms used to convey meaning. Such activities ensure that learners focus on both the form and its meaning.
• Affective Activities: These involve tasks where learners express personal opinions or emotions, helping to reinforce the form–meaning connections in real-world contexts.

Steps in Developing Structured Input Activities:

• Reading or Listening Stage: Learners are exposed to sentences structured to focus on specific forms, e.g., “Lily helped an old lady cross the road,” where lexical temporal adverbs are omitted to force focus on verb forms to understand the temporal context.
• Interpretation Stage: Learners focus on interpreting the sentence correctly using the targeted grammatical form, without producing it.
• Feedback Stage: Learners receive minimal feedback, only confirming if their interpretation is correct, without additional information.

3.2. Empirical Research on Processing Instruction

The effect of explicit information and structured input on Spanish object pronoun learning has been studied by VanPatten and Oikkenon (1996). According to their findings, structured input activities significantly improve learners’ ability to process input more effectively than explicit information alone. To be specific, structured input can alter L2 learners’ processing strategies and help them comprehend and produce language more effectively.

Further studies (e.g., Benati, 2004a; Wong, 2004) support these findings, demonstrating the crucial role of structured input in facilitating both comprehension and production of various grammatical forms across different languages (see

Table 2. Summary of studies on structured input.

Author/s	Target Form/s	Participants Number and L1	Results
VanPatten and Oikkenon (1996)	Spanish object pronouns	59 English	PI and SI groups performed better than EI in interpretation; PI performed best in production
Benati (2004a, 2004b)	Italian future tense, adjective gender agreement	67 English	Structured input as effective as PI in both interpretation and production
Wong (2004)	French negative + indefinite articles	94 English	Structured input critical for improvement

).

Overall, these results suggest that although explicit information benefits students, the transformative power of processing instruction is primarily derived from structured input activities. Students benefit from these activities by moving away from ineffective processing strategies, which enhances their ability to comprehend and use language effectively.

In both offline and online studies, structured input activities have demonstrated significant effectiveness in improving second language acquisition. A variety of linguistic features are examined in these studies, as well as the unique processing challenges faced by language learners, offering valuable insights into language instruction.

3.3. Empirical Research on Referential vs. Affective Structured Input Activities

Referential activities are designed to enhance learners’ understanding of specific grammatical forms through tasks that require correct interpretation based on the grammatical cues present in the input. This direct focus on form helps establish precise form–meaning connections essential for grammatical acquisition.

Affective activities involve tasks that encourage learners to express personal opinions or emotions related to the input. These activities aim to deepen the form–meaning connections by integrating the target grammatical forms within meaningful communicative contexts. There are limited number of studies comparing the effects of these two types of activities (see

Table 3. Summary of studies on referential vs. affective activities.

Author/s	Tests	Comparison	Target Form/s	Participants Number and L1	Results
Henshaw (2012)	Offline sentence-level recognition and interpretation tasks	Referential vs. Affective vs. Combined	Spanish subjunctive	103 native English speakers	All forms effective; Combined most beneficial for retention
Robayna (2020)	Offline and online sentence-level interpretation	Referential vs. Affective vs. Combined	Spanish OVS and past tense	62 native English speakers	Combined approach most effective for learning and retention

).

These studies indicate that while both referential and affective activities are effective, the combination of both tends to yield the best outcomes in terms of both immediate learning gains and long-term retention. This suggests a synergistic effect in which the form-focused referential activities establish the foundational understanding necessary for effective language processing, which is then enriched and solidified through the communicative use facilitated by affective activities.

3.4. Research on Processing Instruction for English Past Tense Markers

For the specific area of English past tense learning, processing instruction has consistently been shown to be superior to traditional instructional methods and meaning-based output instruction (see

Table 4. Summary of studies on processing instruction for English past tense.

Author/s	Participants’ L1	Comparison with	Assessment	Results
Benati (2005)	Chinese, Greek	Traditional Instruction	Sentence-level interpretation and production	PI more effective than other methods
Benati et al. (2008)	Korean	Traditional Instruction	Sentence-level interpretation and production	PI improves processing more than TI
Benati and Lee (2010)	Chinese	Traditional Instruction & Control	Discourse-level interpretation	PI superior at both sentence and discourse levels
Benati and Angelovska (2015)	German	Age comparison	Sentence-level interpretation	Adults show better results than children

).

The results of these studies demonstrate that processing instruction increases learners’ proficiency in processing and using English past tense markers and facilitates a more comprehensive understanding of how language works across contexts and complexities. Learning linguistic skills is enhanced through the structured approach of PI, which emphasizes the connections between form and meaning and provides targeted input that highlights these connections.

The empirical evidence suggests that both referential and affective structured input activities, as well as processing instruction methodology, can improve second language acquisition. The approaches provide solid frameworks for language educators seeking to enhance their teaching strategies and improve learners’ grammatical competence and language proficiency.

This study was motivated by the obvious need to better understand the differences between referential and affective structured input activities on the acquisition of English past tense markers, particularly when assessed through online methods. Online testing methodologies, like self-paced reading tests, aim to provide information about real-time processing behaviors and in-depth processing capacities among L2 learners that offline studies may not be able to capture.

Advantages of Structured Input: Previous research has robustly demonstrated that structured input, as a component of processing instruction, significantly outperforms other instructional strategies like textual enhancement and traditional instruction. This superiority is evident across a variety of languages and linguistic features, particularly in addressing issues related to redundancy and the positioning of elements within sentences. structured input activities have been shown not only to improve immediate comprehension and processing of target forms but also to facilitate the long-term integration of these forms into learners’ spontaneous speech production.

Gaps in Current Research: Despite the established effectiveness of sitructured input, there exists a scarcity of research focusing on the isolated and combined effects of referential and affective activities within this framework, especially studies utilizing online methodologies. The limited and conflicting findings from existing studies underscore the necessity for further research to explore how these two types of activities influence language acquisition and processing in real-time settings.

Research Questions

To address these gaps and extend the understanding of how different types of structured input activities affect the acquisition of English past tense markers, the study poses the following research questions:

• Accuracy of Interpretation: Do L2 learners exposed to three different structured input treatments (referential only, affective only, combination of referential and affective) equally improve their capacity to interpret English past tense markers as measured by accuracy?
• Response Time: Do these treatments affect the learners’ response times in interpreting English past tense markers?
• Processing Time: Do learners spend equal time processing English past tense forms at the word level across these treatments?

4. Research Design

The research utilized a self-paced reading test to investigate the real-time processing effects of both referential and affective activities, analyzed separately and together. This approach facilitates an accurate assessment of how swiftly and effectively learners can understand and process sentences with English past tense markers, offering valuable insights into the effectiveness of each type of structured input activity. The self-paced reading method was selected as the primary assessment tool due to its unique strengths in psycholinguistic research. Specifically, SPR excels at capturing subtle, immediate differences in processing at the word level, making it ideal for isolating real-time effects of grammatical forms like the English past tense “-ed”. Its flexibility supports controlled classroom-based online administration, enabling efficient data collection in educational settings without specialized lab equipment. Furthermore, SPR has established validity in L2 processing studies, as demonstrated by Jegerski (2013), who outlines its application in measuring sentence comprehension dynamics while minimizing explicit knowledge interference. SPR enables fine-grained tracking of reaction times for key sentence elements, making it possible to pinpoint the processing of the target grammatical form while reducing reliance on conscious rule recall.

4.1. Participants

All participants were native Chinese speakers from a first-year senior high class in Weifang City, Shandong Province. Among the 33 students selected for the final dataset, three criteria were met: unfamiliarity with the linguistic feature under study, pretest scores below 50%, and full participation in all phases of the study, including the pre- and immediate post-self-paced reading tests. There were 36 students in the original participant pool. The specific number of students in each group is shown in

Table 5. Number of participants in each group.

Group Description	Number of Participants
Group One (Referential)	8
Group Two (Affective)	7
Group Three (Referential + Affective)	8
Group Four (Control)	10

. Participants were included only if their pretest accuracy on the target feature was below 50%, ensuring comparable baseline knowledge. While no standardized proficiency test was administered, this criterion served as a practical proxy for initial equivalence. Future research should incorporate standardized proficiency measures to enhance comparability across groups.

Ethical Considerations

Informed consent was obtained from all participants and their guardians, with consent forms provided in both English and Chinese. Participants received small incentives—two pieces of chocolate on the first day and two pens on the second day posttesting. It was confirmed with the class English teacher that no lessons on the tense being studied were taught during the experiment week.

4.2. Target Linguistic Feature

This study centers on the English simple past tense, chosen due to specific processing challenges it presents for second language learners. L2 learners often rely on temporal adverbials, such as “Yesterday,” instead of verbal inflections like “-ed,” to infer tense, which may lead to overlooking crucial grammatical markers. The preference for processing information is influenced by a tendency to prioritize lexical cues over grammatical cues when both provide similar semantic information. Furthermore, the Preference for Non-redundancy Principle indicates that if a lexical time indicator is present, processing a verbal inflection may appear unnecessary. The Sentence Location Principle (VanPatten, 2004) further complicates this by indicating that learners typically process sentence elements at the beginning more thoroughly than those at the end or middle, which can result in the under-processing of past tense markers appearing later in a sentence. A sample of the verbs used in this study is listed in

Table 6. Target verbs for structured input activities.

Scheme No.	Target Verb
1	walk
2	jump
3	visit
4	help
5	finish
6	clean
7	push
8	kick
9	lock
10	watch

.

4.3. Overall Procedure

The study employed a pretest–posttest design, conducted entirely online using self-paced reading tests to measure the effects of structured input on English past tense acquisition. Participants were randomly assigned into four instructional groups, three of which received a specific type of treatment. The experimental sessions spanned two sessions within the same week: the pretest on Monday evening and the instructional treatment followed by the immediate posttest on Thursday evening. Randomization was conducted within the intact class by assigning participants to groups using a random number generator, ensuring that all met the inclusion criteria.

The choice of evening sessions was necessitated by the typical 45 min class duration in Mainland Chinese high schools, which is insufficient for the 100 min instructional period required for this study. This scheduling ensured that the full experimental protocol was accommodated without disrupting regular school activities.

The instructional treatment varied across groups, focusing on different types of structured input activities:

• Group One (Referential): Engaged in activities that emphasized grammatical forms necessary for constructing meaning.
• Group Two (Affective): Participated in tasks that involved expressing personal reactions or emotions, linking feelings with the grammatical forms.
• Group Three (Combined Structured Input): Received both referential and affective activities, integrating form-focused and communicative approaches.
• Group Four (Control): Received no specific instruction related to the study’s focus.

4.4. Instructional Treatments

Participants were allocated into four groups, with three engaging in distinct structured input activities—referential, affective, and a combination of both—and a control group receiving no targeted instruction. The design ensured that no prior knowledge of the past tense feature was given to any group, with feedback restricted to correct or incorrect responses. Instructional materials utilized high-frequency vocabulary familiar to the participants, ensuring uniform exposure across all groups to the target linguistic form. The study’s structured input activities, adhering to the principles outlined by Lee and VanPatten (1995), focused on enabling participants to deduce verb tenses without temporal adverbials, relying solely on verbal inflections.

Referential Activities: Participants read English sentences stripped of temporal adverbs, necessitating reliance on verb inflections to determine tense. Post-response, immediate feedback indicated the correctness of their choice. For example, in the sentence “Mike joined the youth club with his classmates,” participants would select whether the event occurred in the past, present, or if they were unsure, with corresponding feedback provided based on their selection.

Affective Activities: These activities prompted participants to relate personally to the sentences read, such as “I visited my grandparents last week,” and to respond if they had engaged in a similar activity. Feedback was provided based on their answers, reinforcing the correct usage of past tense forms.

4.5. Self-Paced Reading Test

The pretest and posttest were conducted in the computer room at Weifang First Middle School using a self-paced reading (SPR) task format. Each test comprised fifty sentences, including ten target items and forty distractor sentences to minimize focus on the target feature.

4.5.1. SPR Task Design

Participants were instructed to read sentences as quickly as possible to limit the influence of explicit knowledge. Sentences were presented one word at a time; pressing the space bar caused the next word to appear and the previous one to disappear. The order of the sentences was randomized using PsychoPy 2023.2.3 software, ensuring unique sequence exposure for each participant. Reaction times were recorded for each word, providing data on cognitive processing speeds.

4.5.2. Rationale for SPR Methodology

The SPR task is ideal for analyzing cognitive processing in real time as participants parse sentences. As noted by Jegerski (2013), longer reading times typically indicate deeper processing. Any changes in processing a linguistic feature should manifest as variations in reading times between pre- and posttests. Specifically, longer reading times at the past tense verb forms post-treatment would suggest heightened awareness of these features.

4.5.3. Sample and Testing Procedure

An example SPR test sentence is: “John fixed the toy for his sister.” Post-treatment, increased reading times for the target verb “fixed” would indicate an enhanced awareness of the past tense form. Conversely, unchanged reading times would imply no significant processing adjustments due to the instructional interventions.

4.5.4. Testing Format

Both pre- and posttests followed the same format, conducted three days apart, with participants again urged to read swiftly. The session concluded with a multiple-choice question assessing temporal comprehension, triggered by a final space bar press.

Figure 1, Figure 2 and Figure 3 demonstrates SPR Task:

The above streamlined methodology ensures clarity in presenting how the SPR tasks were structured and how they contribute to understanding the effectiveness of the instructional interventions.

4.6. Data Analysis

The self-paced reading tests employed in this study are integral to reaction time (RT) research, with RT measurements captured using the PsychoPy software. This software allows for precise recording of the time participants spend on each word during the SPR tests. These tests can be hosted and accessed via pavlovia.org, enabling convenient participant access through a customized link. Post-completion, data is automatically stored within the designer’s account. Before conducting parametric tests, Shapiro–Wilk normality checks were applied to all dependent variables, confirming that assumptions for ANCOVA and paired-sample t-tests were met. One-way ANOVAs on pretest scores confirmed no significant pre-treatment differences among groups.

This study focused on analyzing RT at key sentence positions to evaluate instructional impact. The RTs for the target verb (V) and the subsequent two words (V + 1, V + 2), are of particular interest due to the potential spill-over effect, where changes in processing may not appear immediately at the target word but rather one or two words later.

For statistical analysis, a paired sample t-test was conducted for within-group comparisons, and ANCOVA was utilized for between-group comparisons, aiming to identify any significant differences in RT before and after treatment. Extreme data points were excluded based on common SPR criteria (Chan, 2012), including any RTs shorter than 100 ms or longer than 2500 ms, and participant data with pretest comprehension accuracy over 50%.

This methodological approach underscores the utility of SPR as a tool to investigate sentence processing dynamics, specifically looking at how instructional interventions influence reading and processing speeds and accuracy in tense recognition. The setup aims to illustrate not only immediate comprehension but also the subtle influences of teaching methods on linguistic processing over time.

5. Results and Discussion

5.1. Accuracy of Responses

Table 7. Accuracy data.

Group	Pretest Mean	Posttest Mean	Pretest SD	Posttest SD
Referential	2.727	8.182	4.523	3.917
Affective	3.107	4.143	1.474	2.235
Referential + Affective	3.094	8.781	1.838	1.809
Control	2.975	3.275	1.310	1.536

outlines the descriptive statistics reflecting accuracy improvements from pretest to posttest, revealing significant advancements for Groups One (referential-only) and Three (referential + affective), as opposed to the minimal changes observed in Group Two (affective-only) and Group Four (control). Initial similarities in group performance were confirmed by a one-way ANOVA on pretest accuracy data (see

Table 8. One-way ANOVA for pretest accuracy.

Source	df	F	p-Value	η2
Between Groups	3	0.443	0.723	0.039
Within Groups	33

), showing no significant pre-existing differences among groups [F(3, 33) = 0.443, p = 0.723]. The Shapiro–Wilk test confirmed normality of the accuracy data for all groups (p > 0.05), ensuring the appropriateness of parametric tests (see

Table 9. Shapiro–Wilk normality tests for dependent variables.

Group	Pretest W	Pretest p-Value	Posttest W	Posttest p-Value
Referential	0.921	0.412	0.934	0.489
Affective	0.947	0.576	0.928	0.451
Referential + Affective	0.936	0.498	0.951	0.602
Control	0.943	0.531	0.939	0.512

).

Statistical Analysis

Post-intervention, a repeated-measures ANOVA was conducted with factors for instruction type and time. As shown in

Table 10. Repeated-measures ANOVA for posttest accuracy.

Source	df	F	p-Value	η2
Time (Pre vs. Post)	1, 33	6.931	0.009	0.174
Group	3, 33	7.013	<0.001	0.389
Time × Group	3, 33	2.214	0.105	0.167

, significant differences were found both among groups [F(3, 33) = 7.013, p < 0.001] and from pretest to posttest [F(3, 33) = 6.931, p = 0.009].

Post hoc analyses using the Scheffe test revealed statistically significant distinctions among the groups, indicating the efficacy of specific instructional methods on accuracy:

• Group One vs. Group Two: p = 0.032
• Group One vs. Group Three: p = 0.146
• Group One vs. Group Four: p < 0.001
• Group Two vs. Group Three: p = 0.027
• Group Two vs. Group Four: p = 0.034
• Group Three vs. Group Four: p = 0.015

Accuracy Improvements

Both Groups One and Three showed over 50% improvement in processing English past tense markers accurately, while Group Two exhibited a modest 10% improvement. Group Four showed no significant change. The overall pattern of performance suggests that combined instructional strategies (referential + affective) equaled the effectiveness of referential strategies alone, both surpassing the affective-only and control groups.

5.2. Analysis of Response Time Data

Pretest Consistency Across Groups

As shown in

Table 11. Response time data.

Group	Pretest Mean (ms)	Posttest Mean (ms)	Pretest SD	Posttest SD
Referential	4875.150	3424.757	3958.881	4084.260
Affective	4769.467	4090.778	2161.974	2664.617
Referential + Affective	5255.143	2958.264	4349.739	1292.627
Control	3452.215	3227.660	991.097	1353.885

and

Table 12. One-way ANOVA for pretest response time.

Source	df	F	p-Value	η2
Between Groups	3	0.738	0.159	0.063
Within Groups	33

, initial response times across the four instructional groups were statistically analyzed using a one-way ANOVA, revealing no significant differences at the outset of the study [F(3, 33) = 0.738, p = 0.159]. The Shapiro–Wilk test (see

Table 13. Shapiro–Wilk test results for response time data.

Group	Pretest W	Pretest p-Value	Posttest W	Posttest p-Value
Referential	0.917	0.398	0.926	0.447
Affective	0.941	0.532	0.933	0.476
Referential + Affective	0.929	0.453	0.948	0.589
Control	0.938	0.507	0.944	0.536

) confirmed normality for response time data (p > 0.05). This uniformity ensures that any posttest differences in response times can be attributed to the instructional treatments rather than baseline discrepancies among the groups.

Posttest Response Time Variations

Subsequent analyses compared response times from pretest to posttest. A repeated-measures ANOVA (see

Table 14. Repeated-measures ANOVA for posttest response time.

Source	df	F	p-Value	η2
Time (Pre vs. Post)	1, 33	6.688	0.001	0.169
Group	3, 33	5.122	0.003	0.318
Time × Group	3, 33	2.083	0.119	0.159

) with factors for instructional group and time revealed significant differences [F(3, 33) = 5.122, p = 0.003 for groups; F(3, 33) = 6.688, p = 0.001 for time].

Post hoc Scheffe tests indicated significant interactions:

• Groups One and Three: No significant difference (p = 0.735), suggesting similar efficacy in reducing response times.
• Groups Two and Four: No significant difference (p = 0.539), indicating unaffected response times by the treatments.
• Group One vs. Group Four: Significant reduction in Group One (p = 0.023).
• Group Three vs. Group Four: Significant reduction in Group Three (p = 0.016).

Detailed Findings

Significant reductions in response times were noted for Groups One (referential-only) and Three (referential + affective), with Group One showing a reduction of at least 1400 milliseconds, and Group Three showing an even more substantial reduction of 2200 milliseconds from pretest to posttest. Conversely, participants in Group Two (affective-only) showed no significant change, aligning closely with the control group’s results.

The data demonstrate that referential and combined referential + affective treatments significantly enhance the speed of sentence interpretation concerning English past tense markers, suggesting a more efficient processing and understanding of grammatical structures due to these instructional interventions. The results underscore the potential of targeted structured input activities to markedly improve linguistic processing efficiency in L2 learners.

5.3. Reaction Time Analysis for Sentence Components

5.3.1. Reaction Time for Target Verb

According to

Table 15. Reaction time for the target verb.

Group	Pretest Mean (ms)	Posttest Mean (ms)	Pretest SD	Posttest SD
Referential	552.843	570.282	346.812	424.176
Affective	554.526	558.997	246.997	321.582
Referential + Affective	542.753	665.159	400.362	353.129
Control	524.400	536.493	359.595	481.812

, the descriptive statistics show the mean reaction times and standard deviations for each group at both the pretest and posttest stages. Initial analysis with a one-way ANOVA (

Table 16. One-way ANOVA for pretest target verb reaction time.

Source	df	F	p-Value	η2
Between Groups	3	1.679	0.172	0.134
Within Groups	33

) revealed no significant pre-treatment differences in RT across the four groups [F(3, 33) = 1.679, p = 0.172]. Furthermore, the Shapiro–Wilk test (

Table 17. Shapiro–Wilk test results for target verb reaction time.

Group	Pretest W	Pretest p-Value	Posttest W	Posttest p-Value
Referential	0.924	0.423	0.930	0.465
Affective	0.945	0.561	0.936	0.498
Referential + Affective	0.933	0.476	0.947	0.576
Control	0.940	0.519	0.942	0.528

) confirmed that the assumption of normality was met (p > 0.05).

Post-treatment comparisons indicated significant RT changes between the pretest and posttest within some groups but not others. Group One (Referential-only) and Group Two (Affective-only) showed no significant change in RT [p = 0.377 and p = 0.463, respectively], while Group Three (Referential + Affective) displayed a notable increase in RT [p = 0.002], suggesting a deeper processing of the target verbs post-treatment. Group Four (Control) showed no significant RT changes [p = 0.416].

5.3.2. Reaction Time for V + 1

As shown in

Table 18. Reaction time for V + 1.

Group	Pretest Mean (ms)	Posttest Mean (ms)	Pretest SD	Posttest SD
Referential	525.500	643.394	239.220	460.916
Affective	512.390	490.096	223.776	303.084
Referential + Affective	456.222	596.813	252.974	418.954
Control	503.025	518.840	302.442	409.371

, the descriptive statistics provide the mean reaction times and standard deviations for each group at both the pretest and posttest stages. Pre-treatment comparisons indicated no significant differences across groups [F(3, 33) = 0.957, p = 0.372] (

Table 19. One-way ANOVA for pretest V + 1 reaction time.

Source	df	F	p-Value	η2
Between Groups	3	0.957	0.372	0.087
Within Groups	33

). In addition, the Shapiro–Wilk test confirmed the assumption of normality (p > 0.05;

Table 20. Shapiro–Wilk test results for V + 1 reaction time.

Group	Pretest W	Pretest p-Value	Posttest W	Posttest p-Value
Referential	0.928	0.446	0.923	0.419
Affective	0.943	0.531	0.940	0.519
Referential + Affective	0.937	0.503	0.929	0.453
Control	0.946	0.553	0.941	0.524

).

Post-treatment analysis revealed significant RT increases in Group One [p = 0.003], with Group Three also showing substantial RT prolongation [p < 0.001], indicating enhanced focus on V + 1 following treatment. In contrast, Groups Two and Four exhibited no significant RT changes [p = 0.298 and p = 0.374, respectively].

5.3.3. Reaction Time for V + 2

As shown in

Table 21. Reaction time for V + 2.

Group	Pretest Mean (ms)	Posttest Mean (ms)	Pretest SD	Posttest SD
Referential	489.694	452.510	238.318	276.047
Affective	550.831	534.487	294.998	328.144
Referential + Affective	479.658	510.795	353.827	278.021
Control	504.155	483.078	325.089	355.575

, the descriptive statistics summarize the mean reaction times and standard deviations for each group at both the pretest and posttest stages. No significant differences were noted among groups before treatment [F(3, 33) = 0.457, p = 0.148] (

Table 22. One-way ANOVA for pretest V + 2 reaction time.

Source	df	F	p-Value	η2
Between Groups	3	0.457	0.148	0.043
Within Groups	33

). Furthermore, the Shapiro–Wilk test confirmed that the data met the assumption of normality (p > 0.05;

Table 23. Shapiro–Wilk test results for V + 2 reaction time.

Group	Pretest W	Pretest p-Value	Posttest W	Posttest p-Value
Referential	0.931	0.461	0.927	0.442
Affective	0.939	0.512	0.935	0.493
Referential + Affective	0.944	0.538	0.951	0.597
Control	0.942	0.526	0.943	0.517

).

Post-treatment data show no significant RT changes for any group, indicating a consistent approach to processing V + 2 position across treatments.

Table 24. Region-level paired t-tests (pre vs. post within groups).

Dependent Variable	Group	t(df)	p	Direction
RT at V	Referential	t(7) = 0.94	0.377	n.s.
RT at V	Affective	t(6) = 0.78	0.463	n.s.
RT at V	Referential + Affective	t(7) = 4.92	0.002	↑
RT at V	Control	t(9) = 0.85	0.416	n.s.
RT at V + 1	Referential	t(7) = 4.12	0.003	↑
RT at V + 1	Affective	t(6) = 1.12	0.298	n.s.
RT at V + 1	Referential + Affective	t(7) = 6.43	<0.001	↑
RT at V + 1	Control	t(9) = 0.92	0.374	n.s.
RT at V + 2	All groups	—	>0.100	n.s.

Note. n.s. = not significant; ↑ = significant increase in RT from pre- to post-test.

summarizes the results of region-level paired t-tests comparing pre- and post-treatment reaction times within groups.

The data indicate that structured instruction, particularly when combining referential and affective elements, significantly enhances the attention that participants pay to key linguistic elements within sentences. Notably, the referential and combined groups demonstrated increased RTs at both the target verb and V + 1 positions, suggestive of more deliberate processing and possibly deeper comprehension post-treatment. However, no significant RT changes were observed at the V + 2 positions, indicating a focused effect of the instructional intervention.

5.4. Discussion

This experimental study examined the impact of structured input activities on L2 learners’ online processing of English past tense markers. A self-paced reading test measured accuracy and response times across three instructional groups, addressing three critical research questions regarding the efficacy of referential, affective, and combined instructional treatments (see Section 1 for SPR methodology). The greater effectiveness of referential and combined treatments aligns with VanPatten’s Input Processing Theory: referential tasks compel learners to attend directly to grammatical cues to derive meaning, fostering stronger form–meaning connections. The lack of additional advantage for combined tasks in the immediate posttest may reflect the short time window and the reduced opportunity for affective tasks to exert influence without rich communicative context. This aligns with Henshaw (2012) and Robayna (2020), who found that combined treatments often show their greatest benefits in retention or spontaneous production tasks.

Comparison with Previous Research

The superior performance of the referential and combined groups in accuracy and response time aligns with prior studies. Benati (2005) and Benati et al. (2008) found that processing instruction (PI), particularly with structured input, outperformed traditional instruction for English past tense acquisition among Chinese and Korean EFL learners. Similarly, this study’s results indicate that referential tasks, by forcing attention to verb morphology (e.g., “-ed”), enhance learners’ ability to process grammatical forms, supporting VanPatten’s Primacy of Meaning Principle. The modest improvement in the affective-only group (10% accuracy increase) mirrors findings by Henshaw (2012), where affective activities alone were less effective for immediate grammatical processing but contributed to retention when combined with referential tasks. Unlike Robayna (2020), who found the combined approach most effective for Spanish OVS and past tense, this study found no significant difference between referential-only and combined groups, possibly due to the shorter instructional period (one week vs. longer interventions in Robayna’s study) or the specific challenges of English past tense for Chinese EFL learners, whose L1 lacks tense inflection.

The increased reaction times (RTs) at the target verb and V + 1 positions for the referential and combined groups suggest deeper processing, consistent with Jegerski (2013), who noted that longer RTs indicate heightened attention to linguistic forms. This contrasts with the affective-only and control groups, where RTs remained unchanged, indicating minimal impact on processing strategies. The absence of RT changes at V + 2 aligns with the spill-over effect described by Chan (2012), where processing effects may manifest one or two words after the target, but not further. This suggests that the instructional interventions specifically enhanced attention to the verb and its immediate context, rather than broader sentence processing.

Reasons for Similarities and Differences

The similarities with Benati (2005) and Benati et al. (2008) likely stem from the shared focus on structured input and the use of tasks that prioritize form–meaning connections, particularly for learners whose L1 lacks inflectional morphology. The differences, such as the lack of superiority of the combined approach over referential-only, may be attributed to methodological factors. First, the short duration of the intervention (two sessions within one week) may have limited the affective tasks’ ability to foster deeper communicative engagement, as affective activities often require extended exposure to yield significant effects (Henshaw, 2012). Second, the Chinese L1 participants’ reliance on lexical cues (e.g., temporal adverbs) over grammatical markers, as predicted by VanPatten’s Preference for Non-redundancy Principle, likely amplified the effectiveness of referential tasks, which explicitly target verb morphology. The SPR methodology, which minimizes explicit knowledge interference, may have further highlighted the strengths of referential tasks by capturing real-time processing improvements.

The lack of significant improvement in the affective-only group could be due to the reduced emphasis on form-focused processing, as affective tasks prioritize personal engagement over grammatical accuracy. This aligns with VanPatten (2004), who argues that learners prioritize meaning over form unless explicitly directed otherwise. The control group’s lack of improvement is expected, as they received no targeted instruction, consistent with prior PI studies (e.g., Benati & Lee, 2010).

Critical Analysis and Implications

The findings suggest that referential tasks are particularly effective for initial acquisition of English past tense markers among Chinese EFL learners, likely because they counteract the tendency to overlook verb morphology in favor of lexical cues. However, the lack of additional benefit from combining referential and affective tasks in the immediate posttest raises questions about the optimal balance of these activities. Future research could explore longer intervention periods to determine if affective tasks enhance retention when paired with referential tasks over time. Additionally, the increased RTs in the combined group at the target verb and V + 1 positions suggest that combining task types may lead to more deliberate processing, potentially benefiting long-term acquisition, as suggested by Robayna (2020).

The study’s reliance on SPR provides a methodological advantage over offline tests used in previous studies (e.g., Benati, 2004a), as it captures real-time processing dynamics. However, the ecological validity of SPR is limited, as it isolates word-level processing and may not fully reflect naturalistic language use. This could explain why affective tasks, which rely on communicative context, underperformed compared to expectations from Henshaw (2012). Future studies could integrate SPR with tasks that incorporate richer communicative contexts, such as interactive dialogues, to better assess affective activities’ contributions.

Responses to Research Questions

• RQ1: Accuracy in Interpreting Past Tense Markers

The referential and combined referential + affective groups performed significantly better than affective-only and control groups in interpreting correct past tense sentences. The results were supported by significant improvements from pretest to posttest in these groups, affirming the effectiveness of referential and combined instructional approaches over affective-only instruction. This affirms the effectiveness of referential and combined approaches, aligning with Benati (2005) and VanPatten (2002).

• RQ2: Response Time Improvements

The response times decreased significantly in the referential-only and combined groups from pretest to posttest, suggesting that these treatments enhance processing speed. In contrast, the affective-only and control groups showed no significant change in response time, underscoring the limited impact of affective activities alone on processing efficiency. This supports the superiority of form-focused tasks for immediate processing gains (VanPatten, 2015).

• RQ3: Time Spent on Processing at the Word Level

Significant RT increases at the V + 1 position for referential and combined groups suggest enhanced attention to grammatical forms, consistent with Jegerski (2013). The lack of RT changes at V + 2 indicates a focused effect on the verb and its immediate context, supporting the spill-over effect (Chan, 2012).

6. Conclusions

6.1. Summary of Findings

This study rigorously evaluated the impact of different types of structured input activities—referential, affective, and their combination—on the processing and interpretation of English past tense markers by L2 learners. The findings indicated significant improvements in accuracy and response times, particularly for the groups engaged in referential and combined activities. These groups not only showed enhanced ability to interpret past tense markers accurately but also demonstrated quicker response times, suggesting a more effective processing of the target forms. Moreover, these learners engaged more deeply with the target verb, indicating enhanced cognitive engagement due to structured input activities.

6.2. Contributions to Second Language Acquisition

Empirical Insights: This study contributes valuable empirical insights into how different structured input activities influence the acquisition of grammatical forms known for their processing challenges. The clear differentiation in effectiveness between referential and affective activities enriches our understanding of instructional strategies that can specifically address and ameliorate common learning obstacles.

Methodological Advancements: Introducing a self-paced reading test as a methodological tool in this study opens new avenues for detailed investigation into the cognitive processes involved in grammatical form processing (see Section 1 for SPR details). This approach provides a nuanced view that goes beyond traditional accuracy and error-correction metrics, offering deeper insights into the moment-to-moment processing dynamics inherent in language comprehension. The SPR paradigm captures millisecond-level reaction times to specific sentence regions, allowing precise isolation of grammatical processing effects while minimizing reliance on explicit rule recall.

6.3. Theoretical and Pedagogical Implications

The findings underscore the relevance of structured input in aligning with and enhancing the Input Processing Theory. By effectively redirecting learner attention from default processing strategies that favor lexical cues to more grammatically meaningful elements, structured input activities foster a deeper engagement with language structure. The success of referential activities in this context reaffirms the Primacy of Meaning principle, emphasizing the importance of meaningful engagement with grammatical forms for successful language acquisition.

6.4. Limitations and Future Directions

While this study provides compelling evidence on the efficacy of structured input, it is not without limitations: All participants were Chinese L1 speakers, which limits generalizability to other linguistic backgrounds. The absence of a delayed posttest prevents conclusions about retention effects, particularly for affective and combined treatments that may show advantages over time. Additionally, the SPR paradigm, while precise, reduces ecological validity by minimizing communicative context—potentially underestimating the benefits of affective activities. Future work should incorporate audiovisual or interactive measures to better capture such effects.

• The sample size and homogeneity limit the generalizability of the findings. Future studies should include a more diverse participant pool across different educational contexts and proficiency levels.
• The absence of a delayed posttest to measure retention of learning and longer-term effects of the instruction is a notable gap. Subsequent research should incorporate follow-up assessments to capture these dimensions.
• The focus on only one grammatical feature may not fully represent the broader complexities of language acquisition. Expanding the scope to include other challenging grammatical aspects could provide a more comprehensive understanding of the instructional strategies’ effectiveness.

In summary, this study has made a compelling case for the integration of structured input activities, particularly those that are referentially focused, into language teaching practices to enhance the grammatical competence of L2 learners. The research highlights the specific benefits of different types of structured input, contributing both to theoretical advancements in language acquisition and offering practical insights for educators. These insights can help in designing effective language instruction that caters to the cognitive needs of learners.